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  • C# 4: The Curious ConcurrentDictionary

    - by James Michael Hare
    In my previous post (here) I did a comparison of the new ConcurrentQueue versus the old standard of a System.Collections.Generic Queue with simple locking.  The results were exactly what I would have hoped, that the ConcurrentQueue was faster with multi-threading for most all situations.  In addition, concurrent collections have the added benefit that you can enumerate them even if they're being modified. So I set out to see what the improvements would be for the ConcurrentDictionary, would it have the same performance benefits as the ConcurrentQueue did?  Well, after running some tests and multiple tweaks and tunes, I have good and bad news. But first, let's look at the tests.  Obviously there's many things we can do with a dictionary.  One of the most notable uses, of course, in a multi-threaded environment is for a small, local in-memory cache.  So I set about to do a very simple simulation of a cache where I would create a test class that I'll just call an Accessor.  This accessor will attempt to look up a key in the dictionary, and if the key exists, it stops (i.e. a cache "hit").  However, if the lookup fails, it will then try to add the key and value to the dictionary (i.e. a cache "miss").  So here's the Accessor that will run the tests: 1: internal class Accessor 2: { 3: public int Hits { get; set; } 4: public int Misses { get; set; } 5: public Func<int, string> GetDelegate { get; set; } 6: public Action<int, string> AddDelegate { get; set; } 7: public int Iterations { get; set; } 8: public int MaxRange { get; set; } 9: public int Seed { get; set; } 10:  11: public void Access() 12: { 13: var randomGenerator = new Random(Seed); 14:  15: for (int i=0; i<Iterations; i++) 16: { 17: // give a wide spread so will have some duplicates and some unique 18: var target = randomGenerator.Next(1, MaxRange); 19:  20: // attempt to grab the item from the cache 21: var result = GetDelegate(target); 22:  23: // if the item doesn't exist, add it 24: if(result == null) 25: { 26: AddDelegate(target, target.ToString()); 27: Misses++; 28: } 29: else 30: { 31: Hits++; 32: } 33: } 34: } 35: } Note that so I could test different implementations, I defined a GetDelegate and AddDelegate that will call the appropriate dictionary methods to add or retrieve items in the cache using various techniques. So let's examine the three techniques I decided to test: Dictionary with mutex - Just your standard generic Dictionary with a simple lock construct on an internal object. Dictionary with ReaderWriterLockSlim - Same Dictionary, but now using a lock designed to let multiple readers access simultaneously and then locked when a writer needs access. ConcurrentDictionary - The new ConcurrentDictionary from System.Collections.Concurrent that is supposed to be optimized to allow multiple threads to access safely. So the approach to each of these is also fairly straight-forward.  Let's look at the GetDelegate and AddDelegate implementations for the Dictionary with mutex lock: 1: var addDelegate = (key,val) => 2: { 3: lock (_mutex) 4: { 5: _dictionary[key] = val; 6: } 7: }; 8: var getDelegate = (key) => 9: { 10: lock (_mutex) 11: { 12: string val; 13: return _dictionary.TryGetValue(key, out val) ? val : null; 14: } 15: }; Nothing new or fancy here, just your basic lock on a private object and then query/insert into the Dictionary. Now, for the Dictionary with ReadWriteLockSlim it's a little more complex: 1: var addDelegate = (key,val) => 2: { 3: _readerWriterLock.EnterWriteLock(); 4: _dictionary[key] = val; 5: _readerWriterLock.ExitWriteLock(); 6: }; 7: var getDelegate = (key) => 8: { 9: string val; 10: _readerWriterLock.EnterReadLock(); 11: if(!_dictionary.TryGetValue(key, out val)) 12: { 13: val = null; 14: } 15: _readerWriterLock.ExitReadLock(); 16: return val; 17: }; And finally, the ConcurrentDictionary, which since it does all it's own concurrency control, is remarkably elegant and simple: 1: var addDelegate = (key,val) => 2: { 3: _concurrentDictionary[key] = val; 4: }; 5: var getDelegate = (key) => 6: { 7: string s; 8: return _concurrentDictionary.TryGetValue(key, out s) ? s : null; 9: };                    Then, I set up a test harness that would simply ask the user for the number of concurrent Accessors to attempt to Access the cache (as specified in Accessor.Access() above) and then let them fly and see how long it took them all to complete.  Each of these tests was run with 10,000,000 cache accesses divided among the available Accessor instances.  All times are in milliseconds. 1: Dictionary with Mutex Locking 2: --------------------------------------------------- 3: Accessors Mostly Misses Mostly Hits 4: 1 7916 3285 5: 10 8293 3481 6: 100 8799 3532 7: 1000 8815 3584 8:  9:  10: Dictionary with ReaderWriterLockSlim Locking 11: --------------------------------------------------- 12: Accessors Mostly Misses Mostly Hits 13: 1 8445 3624 14: 10 11002 4119 15: 100 11076 3992 16: 1000 14794 4861 17:  18:  19: Concurrent Dictionary 20: --------------------------------------------------- 21: Accessors Mostly Misses Mostly Hits 22: 1 17443 3726 23: 10 14181 1897 24: 100 15141 1994 25: 1000 17209 2128 The first test I did across the board is the Mostly Misses category.  The mostly misses (more adds because data requested was not in the dictionary) shows an interesting trend.  In both cases the Dictionary with the simple mutex lock is much faster, and the ConcurrentDictionary is the slowest solution.  But this got me thinking, and a little research seemed to confirm it, maybe the ConcurrentDictionary is more optimized to concurrent "gets" than "adds".  So since the ratio of misses to hits were 2 to 1, I decided to reverse that and see the results. So I tweaked the data so that the number of keys were much smaller than the number of iterations to give me about a 2 to 1 ration of hits to misses (twice as likely to already find the item in the cache than to need to add it).  And yes, indeed here we see that the ConcurrentDictionary is indeed faster than the standard Dictionary here.  I have a strong feeling that as the ration of hits-to-misses gets higher and higher these number gets even better as well.  This makes sense since the ConcurrentDictionary is read-optimized. Also note that I tried the tests with capacity and concurrency hints on the ConcurrentDictionary but saw very little improvement, I think this is largely because on the 10,000,000 hit test it quickly ramped up to the correct capacity and concurrency and thus the impact was limited to the first few milliseconds of the run. So what does this tell us?  Well, as in all things, ConcurrentDictionary is not a panacea.  It won't solve all your woes and it shouldn't be the only Dictionary you ever use.  So when should we use each? Use System.Collections.Generic.Dictionary when: You need a single-threaded Dictionary (no locking needed). You need a multi-threaded Dictionary that is loaded only once at creation and never modified (no locking needed). You need a multi-threaded Dictionary to store items where writes are far more prevalent than reads (locking needed). And use System.Collections.Concurrent.ConcurrentDictionary when: You need a multi-threaded Dictionary where the writes are far more prevalent than reads. You need to be able to iterate over the collection without locking it even if its being modified. Both Dictionaries have their strong suits, I have a feeling this is just one where you need to know from design what you hope to use it for and make your decision based on that criteria.

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  • TFS 2010 Basic Concepts

    - by jehan
    v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Here, I’m going to discuss some key Architectural changes and concepts that have taken place in TFS 2010 when compared to TFS 2008. In TFS 2010 Installation, First you need to do the Installation and then you have to configure the Installation Feature from the available features. This is bit similar to SharePoint Installation, where you will first do the Installation and then configure the SharePoint Farms. 1) Installation Features available in TFS2010: a) Basic: It is the most compact TFS installation possible. It will install and configure Source Control, Work Item tracking and Build Services only. (SharePoint and Reporting Integration will not be possible). b) Standard Single Server: This is suitable for Single Server deployment of TFS. It will install and configure Windows SharePoint Services for you and will use the default instance of SQL Server. c) Advanced: It is suitable, if you want use Remote Servers for SQL Server Databases, SharePoint Products and Technologies and SQL Server Reporting Services. d) Application Tier Only: If you want to configure high availability for Team Foundation Server in a Load Balanced Environment (NLB) or you want to move Team Foundation Server from one server to other or you want to restore TFS. e) Upgrade: If you want to upgrade from a prior version of TFS. Note: One more important thing to know here about  TFS 2010 Basic is that,  it can be installed on Client Operations Systems(Windows 7 and Windows Vista SP3), Where as  earlier you cannot Install previous version of TFS (2008 and 2005) on client OS. 2) Team Project Collections: Connect to TFS dialog box in TFS 2008:  In TFS 2008, the TFS Server contains a set of Team Projects and each project may or may not be independent of other projects and every checkin gets a ever increasing  changeset ID  irrespective of the team project in which it is checked in and the same applies to work items  also, who also gets unique Work Item Ids.The main problem with this approach was that there are certain things which were impossible to do; those were required as per the Application Development Process. a)      If something has gone wrong in one team project and now you want to restore it back to earlier state where it was working properly then it requires you to restore the Database of Team Foundation Server from the backup you have taken as per your Maintenance plans and because of this the other team projects may lose out on the work which is not backed up. b)       Your company had a merge with some other company and now you have two TFS servers. One TFS Server which you are working on and other TFS server which other company was working and now after the merge you want to integrate the team projects from two TFS servers into one, which is almost impossible to achieve in TFS 2008. Though you can create the Team Projects in one server manually (In Source Control) which you want to integrate from the other TFS Server, but will lose out on History of Change Sets and Work items and others which are very important. There were few more issues of this sort, which were difficult to resolve in TFS 2008. To resolve issues related to above kind of scenarios which were mainly related TFS Maintenance, Integration, migration and Security,  Microsoft has come up with Team Project Collections concept in TFS 2010.This concept is similar to SharePoint Site Collections and if you are familiar with SharePoint Architecture, then it will help you to understand TFS 2010 Architecture easily. Connect to TFS dialog box in TFS 2010: In above dialog box as you can see there are two Team Project Collections, each team project can contain any number of team projects as you can see on right side it shows the two Team Projects in Team Project Collection (Default Collection) which I have chosen. Note: You can connect to only one Team project Collection at a time using an instance of  TFS Team Explorer. How does it work? To introduce Team Project Collections, changes have been done in reorganization of TFS databases. TFS 2008 was composed of 5-7 databases partitioned by subsystem (each for Version Control, Work Item Tracking, Build, Integration, Project Management...) New TFS 2010 database architecture: TFS_Config: It’s the root database and it contains centralized TFS configuration data, including the list of all team projects exist in TFS server. TFS_Warehouse: The data warehouse contains all the reporting data of served by this server (farm). TFS_* : This contains individual team project collection data. This database contains all the operational data of team project collection regardless of subsystem.In additional to this, you will have databases for SharePoint and Report Server. 3) TFS Farms:  As TFS 2010 is more flexible to configure as multiple Application tiers and multiple Database tiers, so it will be more appropriate to call as TFS Farm if you going for multi server installation of TFS. NLB support for TFS application tiers – With TFS 2010: you can configure multiple TFS application tier machines to serve the same set of Team Project Collections. The primary purpose of NLB support is to enable a cleaner and more complete high availability than in TFS 2008. Even if any application tier in the farm fails then farm will automatically continue to work with hardly any indication to end users of a problem. SQL data tiers: With 2010 you can configure many SQL Servers. Each Database can be configured to be on any SQL Server because each Team Project Collection is an independent database. This feature can also be used to load balance databases across SQL Servers.These new capabilities will significantly change the way enterprises manage their TFS installations in the future. With Team Project Collections and TFS farms, you can create a single, arbitrarily large TFS installation. You can grow it incrementally by adding ATs and SQL Servers as needed.

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  • A Taxonomy of Numerical Methods v1

    - by JoshReuben
    Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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  • How to throttle email server wide on a shared server?

    - by fdsa
    I have multiple programs that send email on a shared server with a relatively low email limit. These programs are completely separate and can each individually throttle mail but cannot do so in relation to the others. Currently, whenever the hourly limit is reached, our host just starts dropping the emails. They say they have no way to change this behavior and basically suggested that I ask around. Does anyone know of any programs that will throttle email server wide on a shared server?

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  • How can I remove python 2.7 after installing python 3.3?

    - by phoenix bai
    I have successfully installed python 3.3 on Ubuntu 12.10. Since I don’t need multiple versions of python, I want to remove the existing python 2.7. When I try to do that, using sudo apt-get remove python2.7 Ubuntu warns me that there are tons of system dependent components which will also be removed. It looks really scary. So, is there a way to remove python 2.7 without removing the system dependent components, or can I direct those dependents to use python 3.3?

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  • Relational Database pioneer Chris Date is giving a seminar 13th/14th May Edinburgh on "SQL and Relat

    - by tonyrogerson
    One of the pioneers of the Relational Database, Chris Date is giving a 2 day seminar in Edinburgh (13th and 14th May 2010) based around his new book "SQL and Relational Theory - How to Write Accurate SQL Code" which if you don't already have I'd say is a must buy. When I first saw this and what he will cover I thought, oh yer - this is going to cost the earth, well it doesn't - its £750 for the two days and there are discounts available for multiple bookings, being a member...(read more)

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  • Another Questionable Article Online…

    - by Jonathan Kehayias
    At the beginning of the month I blogged about my thoughts on the virtualization feedback provided by SSWUG’s newsletter , and Rich responded with some information on how the incorrect information lead him to making incorrect conclusions.  It seems like every couple of weeks an article, tip, newsletter, whatever is posted by or on a major site that has questionable if not outright incorrect material in it.  Last week MSSQLTips posted SQL Server tempdb one or multiple data files in which...(read more)

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  • Class-Level Model Validation with EF Code First and ASP.NET MVC 3

    - by ScottGu
    Earlier this week the data team released the CTP5 build of the new Entity Framework Code-First library.  In my blog post a few days ago I talked about a few of the improvements introduced with the new CTP5 build.  Automatic support for enforcing DataAnnotation validation attributes on models was one of the improvements I discussed.  It provides a pretty easy way to enable property-level validation logic within your model layer. You can apply validation attributes like [Required], [Range], and [RegularExpression] – all of which are built-into .NET 4 – to your model classes in order to enforce that the model properties are valid before they are persisted to a database.  You can also create your own custom validation attributes (like this cool [CreditCard] validator) and have them be automatically enforced by EF Code First as well.  This provides a really easy way to validate property values on your models.  I showed some code samples of this in action in my previous post. Class-Level Model Validation using IValidatableObject DataAnnotation attributes provides an easy way to validate individual property values on your model classes.  Several people have asked - “Does EF Code First also support a way to implement class-level validation methods on model objects, for validation rules than need to span multiple property values?”  It does – and one easy way you can enable this is by implementing the IValidatableObject interface on your model classes. IValidatableObject.Validate() Method Below is an example of using the IValidatableObject interface (which is built-into .NET 4 within the System.ComponentModel.DataAnnotations namespace) to implement two custom validation rules on a Product model class.  The two rules ensure that: New units can’t be ordered if the Product is in a discontinued state New units can’t be ordered if there are already more than 100 units in stock We will enforce these business rules by implementing the IValidatableObject interface on our Product class, and by implementing its Validate() method like so: The IValidatableObject.Validate() method can apply validation rules that span across multiple properties, and can yield back multiple validation errors. Each ValidationResult returned can supply both an error message as well as an optional list of property names that caused the violation (which is useful when displaying error messages within UI). Automatic Validation Enforcement EF Code-First (starting with CTP5) now automatically invokes the Validate() method when a model object that implements the IValidatableObject interface is saved.  You do not need to write any code to cause this to happen – this support is now enabled by default. This new support means that the below code – which violates one of our above business rules – will automatically throw an exception (and abort the transaction) when we call the “SaveChanges()” method on our Northwind DbContext: In addition to reactively handling validation exceptions, EF Code First also allows you to proactively check for validation errors.  Starting with CTP5, you can call the “GetValidationErrors()” method on the DbContext base class to retrieve a list of validation errors within the model objects you are working with.  GetValidationErrors() will return a list of all validation errors – regardless of whether they are generated via DataAnnotation attributes or by an IValidatableObject.Validate() implementation.  Below is an example of proactively using the GetValidationErrors() method to check (and handle) errors before trying to call SaveChanges(): ASP.NET MVC 3 and IValidatableObject ASP.NET MVC 2 included support for automatically honoring and enforcing DataAnnotation attributes on model objects that are used with ASP.NET MVC’s model binding infrastructure.  ASP.NET MVC 3 goes further and also honors the IValidatableObject interface.  This combined support for model validation makes it easy to display appropriate error messages within forms when validation errors occur.  To see this in action, let’s consider a simple Create form that allows users to create a new Product: We can implement the above Create functionality using a ProductsController class that has two “Create” action methods like below: The first Create() method implements a version of the /Products/Create URL that handles HTTP-GET requests - and displays the HTML form to fill-out.  The second Create() method implements a version of the /Products/Create URL that handles HTTP-POST requests - and which takes the posted form data, ensures that is is valid, and if it is valid saves it in the database.  If there are validation issues it redisplays the form with the posted values.  The razor view template of our “Create” view (which renders the form) looks like below: One of the nice things about the above Controller + View implementation is that we did not write any validation logic within it.  The validation logic and business rules are instead implemented entirely within our model layer, and the ProductsController simply checks whether it is valid (by calling the ModelState.IsValid helper method) to determine whether to try and save the changes or redisplay the form with errors. The Html.ValidationMessageFor() helper method calls within our view simply display the error messages our Product model’s DataAnnotations and IValidatableObject.Validate() method returned.  We can see the above scenario in action by filling out invalid data within the form and attempting to submit it: Notice above how when we hit the “Create” button we got an error message.  This was because we ticked the “Discontinued” checkbox while also entering a value for the UnitsOnOrder (and so violated one of our business rules).  You might ask – how did ASP.NET MVC know to highlight and display the error message next to the UnitsOnOrder textbox?  It did this because ASP.NET MVC 3 now honors the IValidatableObject interface when performing model binding, and will retrieve the error messages from validation failures with it. The business rule within our Product model class indicated that the “UnitsOnOrder” property should be highlighted when the business rule we hit was violated: Our Html.ValidationMessageFor() helper method knew to display the business rule error message (next to the UnitsOnOrder edit box) because of the above property name hint we supplied: Keeping things DRY ASP.NET MVC and EF Code First enables you to keep your validation and business rules in one place (within your model layer), and avoid having it creep into your Controllers and Views.  Keeping the validation logic in the model layer helps ensure that you do not duplicate validation/business logic as you add more Controllers and Views to your application.  It allows you to quickly change your business rules/validation logic in one single place (within your model layer) – and have all controllers/views across your application immediately reflect it.  This help keep your application code clean and easily maintainable, and makes it much easier to evolve and update your application in the future. Summary EF Code First (starting with CTP5) now has built-in support for both DataAnnotations and the IValidatableObject interface.  This allows you to easily add validation and business rules to your models, and have EF automatically ensure that they are enforced anytime someone tries to persist changes of them to a database.  ASP.NET MVC 3 also now supports both DataAnnotations and IValidatableObject as well, which makes it even easier to use them with your EF Code First model layer – and then have the controllers/views within your web layer automatically honor and support them as well.  This makes it easy to build clean and highly maintainable applications. You don’t have to use DataAnnotations or IValidatableObject to perform your validation/business logic.  You can always roll your own custom validation architecture and/or use other more advanced validation frameworks/patterns if you want.  But for a lot of applications this built-in support will probably be sufficient – and provide a highly productive way to build solutions. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • 24 Hours of PASS – Database Design Fundamentals

    - by drsql
    Well, I have to admit when I got the invite to speak during this event, I was honored (and still am for that matter). But I have to admit, I hope people don’t come in with any belief that I will be Celebrating SQL Server 2008 R2.  Most of what I will present could have been celebrated with SQL Server 6.5, as I will be doing my bread and butter Database Design Fundamentals session that I have done multiple times over the past few years. Ironically, had the people that you and I work with/for...(read more)

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  • What is Inversion of control and why we need it?

    - by Jalpesh P. Vadgama
    Most of programmer need inversion of control pattern in today’s complex real time application world. So I have decided to write a blog post about it. This blog post will explain what is Inversion of control and why we need it. We are going to take a real world example so it would be better to understand. The problem- Why we need inversion of control? Before giving definition of Inversion of control let’s take a simple real word example to see why we need inversion of control. Please have look on the following code. public class class1 { private class2 _class2; public class1() { _class2=new class2(); } } public class class2 { //Some implementation of class2 } I have two classes “Class1” and “Class2”.  If you see the code in that I have created a instance of class2 class in the class1 class constructor. So the “class1” class is dependent on “class2”. I think that is the biggest issue in real world scenario as if we change the “class2” class then we might need to change the “class1” class also. Here there is one type of dependency between this two classes that is called Tight Coupling. Tight coupling will have lots of problem in real world applications as things are tends to be change in future so we have to change all the tight couple classes that are dependent of each other. To avoid this kind of issue we need Inversion of control. What is Inversion of Control? According to the wikipedia following is a definition of Inversion of control. “In software engineering, Inversion of Control (IoC) is an object-oriented programming practice where the object coupling is bound at run time by an assembler object and is typically not known at compile time using static analysis.” So if you read the it carefully it says that we should have object coupling at run time not compile time where it know what object it will create, what method it will call or what feature it will going to use for that. We need to use same classes in such way so that it will not tight couple with each other. There are multiple way to implement Inversion of control. You can refer wikipedia link for knowing multiple ways of implementing Inversion of control. In future posts we are going to see all the different way of implementing Inversion of control.

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  • CodePlex Daily Summary for Monday, June 14, 2010

    CodePlex Daily Summary for Monday, June 14, 2010New ProjectsBD File Hash: BD File Hash is a convenient file hash and hash compare tool for Windows which currently works with MD5, SHA-1, and SHA-256 algorithms. FileScan: This is an application that searches through a drive or directory structure for files matching a filter. This project was converted from VB to ...genesis9: genesis9HeinanOS: HeinanOS is an operating system developed mainly in C++. HeinanOS is a light OS (1.44 MB image) with a lot of capabilites and many more are being ...MediaBrowserWS - Creates a Web Service for the popular MediaBrowser plugin: Creates a web service in Media Center for accessing your MediaBrowser collection. Allows for external devices (Tablets/phones/laptops) to access a ...MME: New Edition of Managed Menu Extensions for Visual Studio 2010 The Main goal of "MME" is to provide easy access to adding Right Click menus in the ...MVMMapper: Generate the ViewModel and its mapping to the Model when implementing MVVM in .NET. Developed using T4 templates. Current version supports Silver...ProjectArDotNet: Si te agarro te parto! Si te agarro te emperno no me importa que seas menor de edad!Scriptagility for DotNetNuke: Scriptagility is a DotNetNuke module for Javascript developers. This module provides dynamic client scripting infrastructure for developing javascr...simpleLinux Distro: SimpleLinux. is a Linux distributions that is easy to use. Simple Linux website: http://simplelinux.tkTag Cloud Control for asp.net: Tag Cloud Control for asp.net allows the user to display the most important keywords to display in tag cloud. Each Tag has it own navigation url to...thefreeimdb: fsadie qwUppityUp: UppityUp is a simple and light-weight tray application which monitors a remote server and shows a notification when it comes online. This is usefu...Vivid3D 2 - DirectX 10 3D ToolKit: The sequel to my first ever engine wrote several years ago. It is not based on it in anyway. VSIDev: VSI DevXTQXK_WORK: Actionscript 3.0东坡博客: 这是一个ASP。net mvc 2博客。New Releases.NET Extensions - Extension Methods Library: Release 2010.08: Added extension methods for Bitmap manipulation (scaling for now): - Bitmap.ScaleToSize() - Bitmap.ScaleToSizeProportional() - Bitmap.ScaleProport...Black Falcon Software's Database Data-Access-Layers: “SQLHELPER”, “ORAHELPER” - Handling Binary Data: See attached document...BTech Networking Library: BTech Networking Library: Same as pervious just new namespace, extended networking coming soon!!!Community Forums NNTP bridge: Community Forums NNTP Bridge V37: Release of the Community Forums NNTP Bridge to access the social and anwsers MS forums with a single, open source NNTP bridge. This release has ad...Generic Entity Model 2: GEM2 build 54383: This is second BETA release of GEM2! Please see source code change sets for updates! Following implementation is not included in this release: My...Hades: Projet Hadès - Official Demo - Version 0.1.0 Beta: ---------------------------------------------------------------------------- - Projet Hadès - Official Demo - Version 0.1.0 Beta ------------------...HeinanOS: HeinanOS M1 Source Code: You can download HeinanOS M1 Source Code and contribute to HeinanOS development! Be aware that you should not use this code for your own systems! ...HeinanOS: Milestone 1: This is the first major release for HeinanOS 1.0 Please note this is a PRE-RELEASE! This release includes the following features: -Bootable DOS-...HKGolden Express: HKGoldenExpress (Build 201006131900): New features: (None) Bug fix: Incorrect message submit date of message/ replies. (Note: Showing message submit date is enabled since Build 20100...HKGolden Express: HKGoldenExpress (Build 201006140110): New features: (None) Bug fix: (None) Improvements: (None) Other changes: Set time zone of message date as Hong Kong. Adjusted the format of messa...MediaCoder.NET: MediaCoder.NET v1.0 Beta 1.5: Installer file for MediaCoder.NET v1.0 beta 1.5. Now converts multiple files.MME: First release: Features of this release 1. One installer MME.msi. However you can also install MMEMenuManagerSetup.vsix which installs a project template that e...MSBuild Launch Pad (mPad): 1.1 Beta 1: Platform selection box is added.MVMMapper: MVMMapper Release v 1.0.1: This release has no downloadable documentation. Please use the Documentation section to get started.NginxTray: NginxTray 0.7 RC2: NginxTray 0.7 RC2PowerAuras: PowerAuras-3.0.0K-beta3: New Auras: Item Name Equipment Slot Tracking Changes from beta1 5 new aura textures Fixed Tracking bug Added graphical equipment slot sele...PowerAuras: PowerAuras-3.0.0K-beta4: New Auras: Item Name Equipment Slot Tracking Changes from beta1 5 new aura textures Fixed Tracking bug Added graphical equipment slot sele...Scriptagility for DotNetNuke: Scriptagility 1.0 (Beta): Initial public release please evaluate and feedbackSharpDevelop: SharpDevelop 4.0 Beta 1: Release notes: http://community.sharpdevelop.net/forums/t/11388.aspxsimpleLinux Distro: Project X3: This is an example of download for simpleLinuxSOAPI - StackOverflow API Parser/Wrapper Generator: SOAPI Beta 3: The SOAPI Beta 3 download will be made availabe later today when the initial documentation is complete. The previously available Beta 1 download h...Sofa: Initial release V1.0: This is the first release of Sofa. As it is made of code being previously used, as we tested it is a stable release. But bugs are always possible,...Tag Cloud Control for asp.net: Tag Cloud Control for asp.net: Tag Cloud Control for asp.net allows the user to display the most important keywords to display in tag cloud. Each Tag has it own navigation url to...UppityUp: UppityUp v0.1: First functional version, supports monitoring availability by ping (ICMP) requests. Fit for general use. Consists of one standalone .exe file - no...VCC: Latest build, v2.1.30613.0: Automatic drop of latest buildWindStyle ExifInfo for Windows Live Writer: 1.1.0.0: Add: Multiple Language(English and Simplified Chinese); Add: Insert multiple files; Fix: Error when insert pictures without Exif info; Update: Icon...Work Recorder - Hold on own time!: WorkRecorder 1.2: +Add a whole day chartXsltDb - DotNetNuke Module Builder: 01.01.24: Syntax highlighting delivered!New samples for RadControls. On single page you can find RadTreeView, RadRating, RadChart, RadFormDecorator, RadEdito...xUnit.net Contrib: xunitcontrib 0.4 (ReSharper 5.0 RTM + dotCover): xunitcontrib release 0.4 (ReSharper runner) This release provides a test runner plugin for Resharper 5.0, 4.5 and 4.1, targetting all versions of x...Most Popular ProjectsCommunity Forums NNTP bridgeRIA Services EssentialsNeatUploadBxf (Basic XAML Framework)Agile Personal Development Methodology.NET Transactional File ManagerSOLID by exampleASP.NET MVC Time PlannerWEI ShareSiverlight ProjectMost Active ProjectsjQuery Library for SharePoint Web Servicespatterns & practices – Enterprise LibraryNB_Store - Free DotNetNuke Ecommerce Catalog ModuleRhyduino - Arduino and Managed CodeCommunity Forums NNTP bridgeCassandraemonBlogEngine.NETLightweight Fluent WorkflowMediaCoder.NETAndrew's XNA Helpers

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  • SQL Server v.Next (Denali) : Deriving sets using SEQUENCE

    - by AaronBertrand
    One complaint about SEQUENCE is that there is no simple construct such as NEXT (@n) VALUES FOR so that you could get a range of SEQUENCE values as a set. In a previous post about SEQUENCE , I mentioned that to get a range of rows from a sequence, you should use the system stored procedure sys.sp_sequence_get_range . There are some issues with this stored procedure: the parameter names are not easy to memorize; it requires multiple conversions to and from SQL_VARIANT; and, producing a set from the...(read more)

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  • Ancillary Objects: Separate Debug ELF Files For Solaris

    - by Ali Bahrami
    We introduced a new object ELF object type in Solaris 11 Update 1 called the Ancillary Object. This posting describes them, using material originally written during their development, the PSARC arc case, and the Solaris Linker and Libraries Manual. ELF objects contain allocable sections, which are mapped into memory at runtime, and non-allocable sections, which are present in the file for use by debuggers and observability tools, but which are not mapped or used at runtime. Typically, all of these sections exist within a single object file. Ancillary objects allow them to instead go into a separate file. There are different reasons given for wanting such a feature. One can debate whether the added complexity is worth the benefit, and in most cases it is not. However, one important case stands out — customers with very large 32-bit objects who are not ready or able to make the transition to 64-bits. We have customers who build extremely large 32-bit objects. Historically, the debug sections in these objects have used the stabs format, which is limited, but relatively compact. In recent years, the industry has transitioned to the powerful but verbose DWARF standard. In some cases, the size of these debug sections is large enough to push the total object file size past the fundamental 4GB limit for 32-bit ELF object files. The best, and ultimately only, solution to overly large objects is to transition to 64-bits. However, consider environments where: Hundreds of users may be executing the code on large shared systems. (32-bits use less memory and bus bandwidth, and on sparc runs just as fast as 64-bit code otherwise). Complex finely tuned code, where the original authors may no longer be available. Critical production code, that was expensive to qualify and bring online, and which is otherwise serving its intended purpose without issue. Users in these risk adverse and/or high scale categories have good reasons to push 32-bits objects to the limit before moving on. Ancillary objects offer these users a longer runway. Design The design of ancillary objects is intended to be simple, both to help human understanding when examining elfdump output, and to lower the bar for debuggers such as dbx to support them. The primary and ancillary objects have the same set of section headers, with the same names, in the same order (i.e. each section has the same index in both files). A single added section of type SHT_SUNW_ANCILLARY is added to both objects, containing information that allows a debugger to identify and validate both files relative to each other. Given one of these files, the ancillary section allows you to identify the other. Allocable sections go in the primary object, and non-allocable ones go into the ancillary object. A small set of non-allocable objects, notably the symbol table, are copied into both objects. As noted above, most sections are only written to one of the two objects, but both objects have the same section header array. The section header in the file that does not contain the section data is tagged with the SHF_SUNW_ABSENT section header flag to indicate its placeholder status. Compiler writers and others who produce objects can set the SUNW_SHF_PRIMARY section header flag to mark non-allocable sections that should go to the primary object rather than the ancillary. If you don't request an ancillary object, the Solaris ELF format is unchanged. Users who don't use ancillary objects do not pay for the feature. This is important, because they exist to serve a small subset of our users, and must not complicate the common case. If you do request an ancillary object, the runtime behavior of the primary object will be the same as that of a normal object. There is no added runtime cost. The primary and ancillary object together represent a logical single object. This is facilitated by the use of a single set of section headers. One can easily imagine a tool that can merge a primary and ancillary object into a single file, or the reverse. (Note that although this is an interesting intellectual exercise, we don't actually supply such a tool because there's little practical benefit above and beyond using ld to create the files). Among the benefits of this approach are: There is no need for per-file symbol tables to reflect the contents of each file. The same symbol table that would be produced for a standard object can be used. The section contents are identical in either case — there is no need to alter data to accommodate multiple files. It is very easy for a debugger to adapt to these new files, and the processing involved can be encapsulated in input/output routines. Most of the existing debugger implementation applies without modification. The limit of a 4GB 32-bit output object is now raised to 4GB of code, and 4GB of debug data. There is also the future possibility (not currently supported) to support multiple ancillary objects, each of which could contain up to 4GB of additional debug data. It must be noted however that the 32-bit DWARF debug format is itself inherently 32-bit limited, as it uses 32-bit offsets between debug sections, so the ability to employ multiple ancillary object files may not turn out to be useful. Using Ancillary Objects (From the Solaris Linker and Libraries Guide) By default, objects contain both allocable and non-allocable sections. Allocable sections are the sections that contain executable code and the data needed by that code at runtime. Non-allocable sections contain supplemental information that is not required to execute an object at runtime. These sections support the operation of debuggers and other observability tools. The non-allocable sections in an object are not loaded into memory at runtime by the operating system, and so, they have no impact on memory use or other aspects of runtime performance no matter their size. For convenience, both allocable and non-allocable sections are normally maintained in the same file. However, there are situations in which it can be useful to separate these sections. To reduce the size of objects in order to improve the speed at which they can be copied across wide area networks. To support fine grained debugging of highly optimized code requires considerable debug data. In modern systems, the debugging data can easily be larger than the code it describes. The size of a 32-bit object is limited to 4 Gbytes. In very large 32-bit objects, the debug data can cause this limit to be exceeded and prevent the creation of the object. To limit the exposure of internal implementation details. Traditionally, objects have been stripped of non-allocable sections in order to address these issues. Stripping is effective, but destroys data that might be needed later. The Solaris link-editor can instead write non-allocable sections to an ancillary object. This feature is enabled with the -z ancillary command line option. $ ld ... -z ancillary[=outfile] ...By default, the ancillary file is given the same name as the primary output object, with a .anc file extension. However, a different name can be provided by providing an outfile value to the -z ancillary option. When -z ancillary is specified, the link-editor performs the following actions. All allocable sections are written to the primary object. In addition, all non-allocable sections containing one or more input sections that have the SHF_SUNW_PRIMARY section header flag set are written to the primary object. All remaining non-allocable sections are written to the ancillary object. The following non-allocable sections are written to both the primary object and ancillary object. .shstrtab The section name string table. .symtab The full non-dynamic symbol table. .symtab_shndx The symbol table extended index section associated with .symtab. .strtab The non-dynamic string table associated with .symtab. .SUNW_ancillary Contains the information required to identify the primary and ancillary objects, and to identify the object being examined. The primary object and all ancillary objects contain the same array of sections headers. Each section has the same section index in every file. Although the primary and ancillary objects all define the same section headers, the data for most sections will be written to a single file as described above. If the data for a section is not present in a given file, the SHF_SUNW_ABSENT section header flag is set, and the sh_size field is 0. This organization makes it possible to acquire a full list of section headers, a complete symbol table, and a complete list of the primary and ancillary objects from either of the primary or ancillary objects. The following example illustrates the underlying implementation of ancillary objects. An ancillary object is created by adding the -z ancillary command line option to an otherwise normal compilation. The file utility shows that the result is an executable named a.out, and an associated ancillary object named a.out.anc. $ cat hello.c #include <stdio.h> int main(int argc, char **argv) { (void) printf("hello, world\n"); return (0); } $ cc -g -zancillary hello.c $ file a.out a.out.anc a.out: ELF 32-bit LSB executable 80386 Version 1 [FPU], dynamically linked, not stripped, ancillary object a.out.anc a.out.anc: ELF 32-bit LSB ancillary 80386 Version 1, primary object a.out $ ./a.out hello worldThe resulting primary object is an ordinary executable that can be executed in the usual manner. It is no different at runtime than an executable built without the use of ancillary objects, and then stripped of non-allocable content using the strip or mcs commands. As previously described, the primary object and ancillary objects contain the same section headers. To see how this works, it is helpful to use the elfdump utility to display these section headers and compare them. The following table shows the section header information for a selection of headers from the previous link-edit example. Index Section Name Type Primary Flags Ancillary Flags Primary Size Ancillary Size 13 .text PROGBITS ALLOC EXECINSTR ALLOC EXECINSTR SUNW_ABSENT 0x131 0 20 .data PROGBITS WRITE ALLOC WRITE ALLOC SUNW_ABSENT 0x4c 0 21 .symtab SYMTAB 0 0 0x450 0x450 22 .strtab STRTAB STRINGS STRINGS 0x1ad 0x1ad 24 .debug_info PROGBITS SUNW_ABSENT 0 0 0x1a7 28 .shstrtab STRTAB STRINGS STRINGS 0x118 0x118 29 .SUNW_ancillary SUNW_ancillary 0 0 0x30 0x30 The data for most sections is only present in one of the two files, and absent from the other file. The SHF_SUNW_ABSENT section header flag is set when the data is absent. The data for allocable sections needed at runtime are found in the primary object. The data for non-allocable sections used for debugging but not needed at runtime are placed in the ancillary file. A small set of non-allocable sections are fully present in both files. These are the .SUNW_ancillary section used to relate the primary and ancillary objects together, the section name string table .shstrtab, as well as the symbol table.symtab, and its associated string table .strtab. It is possible to strip the symbol table from the primary object. A debugger that encounters an object without a symbol table can use the .SUNW_ancillary section to locate the ancillary object, and access the symbol contained within. The primary object, and all associated ancillary objects, contain a .SUNW_ancillary section that allows all the objects to be identified and related together. $ elfdump -T SUNW_ancillary a.out a.out.anc a.out: Ancillary Section: .SUNW_ancillary index tag value [0] ANC_SUNW_CHECKSUM 0x8724 [1] ANC_SUNW_MEMBER 0x1 a.out [2] ANC_SUNW_CHECKSUM 0x8724 [3] ANC_SUNW_MEMBER 0x1a3 a.out.anc [4] ANC_SUNW_CHECKSUM 0xfbe2 [5] ANC_SUNW_NULL 0 a.out.anc: Ancillary Section: .SUNW_ancillary index tag value [0] ANC_SUNW_CHECKSUM 0xfbe2 [1] ANC_SUNW_MEMBER 0x1 a.out [2] ANC_SUNW_CHECKSUM 0x8724 [3] ANC_SUNW_MEMBER 0x1a3 a.out.anc [4] ANC_SUNW_CHECKSUM 0xfbe2 [5] ANC_SUNW_NULL 0 The ancillary sections for both objects contain the same number of elements, and are identical except for the first element. Each object, starting with the primary object, is introduced with a MEMBER element that gives the file name, followed by a CHECKSUM that identifies the object. In this example, the primary object is a.out, and has a checksum of 0x8724. The ancillary object is a.out.anc, and has a checksum of 0xfbe2. The first element in a .SUNW_ancillary section, preceding the MEMBER element for the primary object, is always a CHECKSUM element, containing the checksum for the file being examined. The presence of a .SUNW_ancillary section in an object indicates that the object has associated ancillary objects. The names of the primary and all associated ancillary objects can be obtained from the ancillary section from any one of the files. It is possible to determine which file is being examined from the larger set of files by comparing the first checksum value to the checksum of each member that follows. Debugger Access and Use of Ancillary Objects Debuggers and other observability tools must merge the information found in the primary and ancillary object files in order to build a complete view of the object. This is equivalent to processing the information from a single file. This merging is simplified by the primary object and ancillary objects containing the same section headers, and a single symbol table. The following steps can be used by a debugger to assemble the information contained in these files. Starting with the primary object, or any of the ancillary objects, locate the .SUNW_ancillary section. The presence of this section identifies the object as part of an ancillary group, contains information that can be used to obtain a complete list of the files and determine which of those files is the one currently being examined. Create a section header array in memory, using the section header array from the object being examined as an initial template. Open and read each file identified by the .SUNW_ancillary section in turn. For each file, fill in the in-memory section header array with the information for each section that does not have the SHF_SUNW_ABSENT flag set. The result will be a complete in-memory copy of the section headers with pointers to the data for all sections. Once this information has been acquired, the debugger can proceed as it would in the single file case, to access and control the running program. Note - The ELF definition of ancillary objects provides for a single primary object, and an arbitrary number of ancillary objects. At this time, the Oracle Solaris link-editor only produces a single ancillary object containing all non-allocable sections. This may change in the future. Debuggers and other observability tools should be written to handle the general case of multiple ancillary objects. ELF Implementation Details (From the Solaris Linker and Libraries Guide) To implement ancillary objects, it was necessary to extend the ELF format to add a new object type (ET_SUNW_ANCILLARY), a new section type (SHT_SUNW_ANCILLARY), and 2 new section header flags (SHF_SUNW_ABSENT, SHF_SUNW_PRIMARY). In this section, I will detail these changes, in the form of diffs to the Solaris Linker and Libraries manual. Part IV ELF Application Binary Interface Chapter 13: Object File Format Object File Format Edit Note: This existing section at the beginning of the chapter describes the ELF header. There's a table of object file types, which now includes the new ET_SUNW_ANCILLARY type. e_type Identifies the object file type, as listed in the following table. NameValueMeaning ET_NONE0No file type ET_REL1Relocatable file ET_EXEC2Executable file ET_DYN3Shared object file ET_CORE4Core file ET_LOSUNW0xfefeStart operating system specific range ET_SUNW_ANCILLARY0xfefeAncillary object file ET_HISUNW0xfefdEnd operating system specific range ET_LOPROC0xff00Start processor-specific range ET_HIPROC0xffffEnd processor-specific range Sections Edit Note: This overview section defines the section header structure, and provides a high level description of known sections. It was updated to define the new SHF_SUNW_ABSENT and SHF_SUNW_PRIMARY flags and the new SHT_SUNW_ANCILLARY section. ... sh_type Categorizes the section's contents and semantics. Section types and their descriptions are listed in Table 13-5. sh_flags Sections support 1-bit flags that describe miscellaneous attributes. Flag definitions are listed in Table 13-8. ... Table 13-5 ELF Section Types, sh_type NameValue . . . SHT_LOSUNW0x6fffffee SHT_SUNW_ancillary0x6fffffee . . . ... SHT_LOSUNW - SHT_HISUNW Values in this inclusive range are reserved for Oracle Solaris OS semantics. SHT_SUNW_ANCILLARY Present when a given object is part of a group of ancillary objects. Contains information required to identify all the files that make up the group. See Ancillary Section. ... Table 13-8 ELF Section Attribute Flags NameValue . . . SHF_MASKOS0x0ff00000 SHF_SUNW_NODISCARD0x00100000 SHF_SUNW_ABSENT0x00200000 SHF_SUNW_PRIMARY0x00400000 SHF_MASKPROC0xf0000000 . . . ... SHF_SUNW_ABSENT Indicates that the data for this section is not present in this file. When ancillary objects are created, the primary object and any ancillary objects, will all have the same section header array, to facilitate merging them to form a complete view of the object, and to allow them to use the same symbol tables. Each file contains a subset of the section data. The data for allocable sections is written to the primary object while the data for non-allocable sections is written to an ancillary file. The SHF_SUNW_ABSENT flag is used to indicate that the data for the section is not present in the object being examined. When the SHF_SUNW_ABSENT flag is set, the sh_size field of the section header must be 0. An application encountering an SHF_SUNW_ABSENT section can choose to ignore the section, or to search for the section data within one of the related ancillary files. SHF_SUNW_PRIMARY The default behavior when ancillary objects are created is to write all allocable sections to the primary object and all non-allocable sections to the ancillary objects. The SHF_SUNW_PRIMARY flag overrides this behavior. Any output section containing one more input section with the SHF_SUNW_PRIMARY flag set is written to the primary object without regard for its allocable status. ... Two members in the section header, sh_link, and sh_info, hold special information, depending on section type. Table 13-9 ELF sh_link and sh_info Interpretation sh_typesh_linksh_info . . . SHT_SUNW_ANCILLARY The section header index of the associated string table. 0 . . . Special Sections Edit Note: This section describes the sections used in Solaris ELF objects, using the types defined in the previous description of section types. It was updated to define the new .SUNW_ancillary (SHT_SUNW_ANCILLARY) section. Various sections hold program and control information. Sections in the following table are used by the system and have the indicated types and attributes. Table 13-10 ELF Special Sections NameTypeAttribute . . . .SUNW_ancillarySHT_SUNW_ancillaryNone . . . ... .SUNW_ancillary Present when a given object is part of a group of ancillary objects. Contains information required to identify all the files that make up the group. See Ancillary Section for details. ... Ancillary Section Edit Note: This new section provides the format reference describing the layout of a .SUNW_ancillary section and the meaning of the various tags. Note that these sections use the same tag/value concept used for dynamic and capabilities sections, and will be familiar to anyone used to working with ELF. In addition to the primary output object, the Solaris link-editor can produce one or more ancillary objects. Ancillary objects contain non-allocable sections that would normally be written to the primary object. When ancillary objects are produced, the primary object and all of the associated ancillary objects contain a SHT_SUNW_ancillary section, containing information that identifies these related objects. Given any one object from such a group, the ancillary section provides the information needed to identify and interpret the others. This section contains an array of the following structures. See sys/elf.h. typedef struct { Elf32_Word a_tag; union { Elf32_Word a_val; Elf32_Addr a_ptr; } a_un; } Elf32_Ancillary; typedef struct { Elf64_Xword a_tag; union { Elf64_Xword a_val; Elf64_Addr a_ptr; } a_un; } Elf64_Ancillary; For each object with this type, a_tag controls the interpretation of a_un. a_val These objects represent integer values with various interpretations. a_ptr These objects represent file offsets or addresses. The following ancillary tags exist. Table 13-NEW1 ELF Ancillary Array Tags NameValuea_un ANC_SUNW_NULL0Ignored ANC_SUNW_CHECKSUM1a_val ANC_SUNW_MEMBER2a_ptr ANC_SUNW_NULL Marks the end of the ancillary section. ANC_SUNW_CHECKSUM Provides the checksum for a file in the c_val element. When ANC_SUNW_CHECKSUM precedes the first instance of ANC_SUNW_MEMBER, it provides the checksum for the object from which the ancillary section is being read. When it follows an ANC_SUNW_MEMBER tag, it provides the checksum for that member. ANC_SUNW_MEMBER Specifies an object name. The a_ptr element contains the string table offset of a null-terminated string, that provides the file name. An ancillary section must always contain an ANC_SUNW_CHECKSUM before the first instance of ANC_SUNW_MEMBER, identifying the current object. Following that, there should be an ANC_SUNW_MEMBER for each object that makes up the complete set of objects. Each ANC_SUNW_MEMBER should be followed by an ANC_SUNW_CHECKSUM for that object. A typical ancillary section will therefore be structured as: TagMeaning ANC_SUNW_CHECKSUMChecksum of this object ANC_SUNW_MEMBERName of object #1 ANC_SUNW_CHECKSUMChecksum for object #1 . . . ANC_SUNW_MEMBERName of object N ANC_SUNW_CHECKSUMChecksum for object N ANC_SUNW_NULL An object can therefore identify itself by comparing the initial ANC_SUNW_CHECKSUM to each of the ones that follow, until it finds a match. Related Other Work The GNU developers have also encountered the need/desire to support separate debug information files, and use the solution detailed at http://sourceware.org/gdb/onlinedocs/gdb/Separate-Debug-Files.html. At the current time, the separate debug file is constructed by building the standard object first, and then copying the debug data out of it in a separate post processing step, Hence, it is limited to a total of 4GB of code and debug data, just as a single object file would be. They are aware of this, and I have seen online comments indicating that they may add direct support for generating these separate files to their link-editor. It is worth noting that the GNU objcopy utility is available on Solaris, and that the Studio dbx debugger is able to use these GNU style separate debug files even on Solaris. Although this is interesting in terms giving Linux users a familiar environment on Solaris, the 4GB limit means it is not an answer to the problem of very large 32-bit objects. We have also encountered issues with objcopy not understanding Solaris-specific ELF sections, when using this approach. The GNU community also has a current effort to adapt their DWARF debug sections in order to move them to separate files before passing the relocatable objects to the linker. The details of Project Fission can be found at http://gcc.gnu.org/wiki/DebugFission. The goal of this project appears to be to reduce the amount of data seen by the link-editor. The primary effort revolves around moving DWARF data to separate .dwo files so that the link-editor never encounters them. The details of modifying the DWARF data to be usable in this form are involved — please see the above URL for details.

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  • Unity: Is there a way to edit a Skin file?

    - by Roberto
    My project has multiple skins and sometimes we have to deal with skins with many custom styles. Editing them in the editor is difficult, for instance, I cannot delete one style that is not the last one without deleting the ones after it. Would there be a way to edit a file that represents this skin? Could I edit a skin file if I use Text in the Asset Serialization Mode (Unity Pro)? If not, is there something in the Unity Store to help me better edit skins?

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  • Coronal Mass Ejection Video Captures Stunning Views of the Sun’s Surface

    - by Jason Fitzpatrick
    This beautiful HD video, courtesy of NASA, captures the Sun’s August 31st Coronal Mass Ejection with multiple angles and techniques–the surface of the Sun can be quite a turbulent place. [via Boing Boing] HTG Explains: What The Windows Event Viewer Is and How You Can Use It HTG Explains: How Windows Uses The Task Scheduler for System Tasks HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows?

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  • Silverlight Cream for March 29, 2010 -- #824

    - by Dave Campbell
    In this Issue: smartyP(-2-), Al Pascual, Mike Taulty, Shawn Burke(-2-), Vikram Pendse, Tomasz Janczuk, Lee, and Alexey Zakharov. Shoutouts: Jeff Weber announced New Silverlight Game “Snow Spill” by Nick Avery of Liserd Arts Games John Papa summarized links to all the Silverlight and Windows Phone 7 Sessions from MIX 10 Tim Heuer has a post up about OData and the MIX10 feed: MIX10: Yet another way to view video content sessions using their OData feed From SilverlightCream.com: Creating a Windows Phone 7 Metro Style Pivot Application [Part 1] smartyP has a two-part video tutorial up on creating a WP7 pivot navigation app using Expression Blend. He's also looking for feedback. Creating a Windows Phone 7 Metro Style Pivot Application [Part 2] In part 2, smartyP adds gestures to his navigation. He also has some good external links listed. Al Pascual: My First Windows Phone 7 Application Al Pascual extends the MIX10 keynote WP7 sample by adding the ability to send tweets ... with all the code. Silverlight 4 RC and the “silent installation” Mike Taulty discusses and demonstrates installing an OOB app without having to visit a webpage to get it. In other words, pass it around on a USB drive, send it in email, etc. iPhone SDK vs Windows Phone 7 Series SDK Challenge, Part 1: Hello World! Shawn Burke has a 2-part series up comparing iPhone and WP7 development looking at how easy it is to code and lines of code produced by the tools. This first post is the classic Hello World. Check out the comments as well. iPhone SDK vs. Windows Phone 7 Series SDK Challenge, Part 2: MoveMe Shawn Burke's part 2 is comparing the classic iPhone 'MoveMe' app... again, check out all the comments. Silverlight 4 : Indic Support in Silverlight Vikram Pendse demonstrates using the Microsoft Indic Language Input tool. He has some screen shots and discussion about fonts in Silverlight. Comparison of HTTP polling duplex and net.tcp performance in Silverlight 4 RC Tomasz Janczuk is checking out Silverlight4 RC and has a comparison up of the performance of the three mechanisms for asynch data push for the server to the client/. Summary rows in Datagrid with multiple groups Lee revisted a post that displayed Summary/Totals in the group header to also support multiple groups now. Silverlight Commands Hacks: Passing EventArgs as CommandParameter to DelegateCommand triggered by EventTrigger Alexey Zakharov suggests a workaround 'InvokeDelegateCommandAction' to keep Blend from ignoring event args. Stay in the 'Light! Twitter SilverlightNews | Twitter WynApse | WynApse.com | Tagged Posts | SilverlightCream Join me @ SilverlightCream | Phoenix Silverlight User Group Technorati Tags: Silverlight    Silverlight 3    Silverlight 4    Windows Phone MIX10

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  • C#/.NET Fundamentals: Choosing the Right Collection Class

    - by James Michael Hare
    The .NET Base Class Library (BCL) has a wide array of collection classes at your disposal which make it easy to manage collections of objects. While it's great to have so many classes available, it can be daunting to choose the right collection to use for any given situation. As hard as it may be, choosing the right collection can be absolutely key to the performance and maintainability of your application! This post will look at breaking down any confusion between each collection and the situations in which they excel. We will be spending most of our time looking at the System.Collections.Generic namespace, which is the recommended set of collections. The Generic Collections: System.Collections.Generic namespace The generic collections were introduced in .NET 2.0 in the System.Collections.Generic namespace. This is the main body of collections you should tend to focus on first, as they will tend to suit 99% of your needs right up front. It is important to note that the generic collections are unsynchronized. This decision was made for performance reasons because depending on how you are using the collections its completely possible that synchronization may not be required or may be needed on a higher level than simple method-level synchronization. Furthermore, concurrent read access (all writes done at beginning and never again) is always safe, but for concurrent mixed access you should either synchronize the collection or use one of the concurrent collections. So let's look at each of the collections in turn and its various pros and cons, at the end we'll summarize with a table to help make it easier to compare and contrast the different collections. The Associative Collection Classes Associative collections store a value in the collection by providing a key that is used to add/remove/lookup the item. Hence, the container associates the value with the key. These collections are most useful when you need to lookup/manipulate a collection using a key value. For example, if you wanted to look up an order in a collection of orders by an order id, you might have an associative collection where they key is the order id and the value is the order. The Dictionary<TKey,TVale> is probably the most used associative container class. The Dictionary<TKey,TValue> is the fastest class for associative lookups/inserts/deletes because it uses a hash table under the covers. Because the keys are hashed, the key type should correctly implement GetHashCode() and Equals() appropriately or you should provide an external IEqualityComparer to the dictionary on construction. The insert/delete/lookup time of items in the dictionary is amortized constant time - O(1) - which means no matter how big the dictionary gets, the time it takes to find something remains relatively constant. This is highly desirable for high-speed lookups. The only downside is that the dictionary, by nature of using a hash table, is unordered, so you cannot easily traverse the items in a Dictionary in order. The SortedDictionary<TKey,TValue> is similar to the Dictionary<TKey,TValue> in usage but very different in implementation. The SortedDictionary<TKey,TValye> uses a binary tree under the covers to maintain the items in order by the key. As a consequence of sorting, the type used for the key must correctly implement IComparable<TKey> so that the keys can be correctly sorted. The sorted dictionary trades a little bit of lookup time for the ability to maintain the items in order, thus insert/delete/lookup times in a sorted dictionary are logarithmic - O(log n). Generally speaking, with logarithmic time, you can double the size of the collection and it only has to perform one extra comparison to find the item. Use the SortedDictionary<TKey,TValue> when you want fast lookups but also want to be able to maintain the collection in order by the key. The SortedList<TKey,TValue> is the other ordered associative container class in the generic containers. Once again SortedList<TKey,TValue>, like SortedDictionary<TKey,TValue>, uses a key to sort key-value pairs. Unlike SortedDictionary, however, items in a SortedList are stored as an ordered array of items. This means that insertions and deletions are linear - O(n) - because deleting or adding an item may involve shifting all items up or down in the list. Lookup time, however is O(log n) because the SortedList can use a binary search to find any item in the list by its key. So why would you ever want to do this? Well, the answer is that if you are going to load the SortedList up-front, the insertions will be slower, but because array indexing is faster than following object links, lookups are marginally faster than a SortedDictionary. Once again I'd use this in situations where you want fast lookups and want to maintain the collection in order by the key, and where insertions and deletions are rare. The Non-Associative Containers The other container classes are non-associative. They don't use keys to manipulate the collection but rely on the object itself being stored or some other means (such as index) to manipulate the collection. The List<T> is a basic contiguous storage container. Some people may call this a vector or dynamic array. Essentially it is an array of items that grow once its current capacity is exceeded. Because the items are stored contiguously as an array, you can access items in the List<T> by index very quickly. However inserting and removing in the beginning or middle of the List<T> are very costly because you must shift all the items up or down as you delete or insert respectively. However, adding and removing at the end of a List<T> is an amortized constant operation - O(1). Typically List<T> is the standard go-to collection when you don't have any other constraints, and typically we favor a List<T> even over arrays unless we are sure the size will remain absolutely fixed. The LinkedList<T> is a basic implementation of a doubly-linked list. This means that you can add or remove items in the middle of a linked list very quickly (because there's no items to move up or down in contiguous memory), but you also lose the ability to index items by position quickly. Most of the time we tend to favor List<T> over LinkedList<T> unless you are doing a lot of adding and removing from the collection, in which case a LinkedList<T> may make more sense. The HashSet<T> is an unordered collection of unique items. This means that the collection cannot have duplicates and no order is maintained. Logically, this is very similar to having a Dictionary<TKey,TValue> where the TKey and TValue both refer to the same object. This collection is very useful for maintaining a collection of items you wish to check membership against. For example, if you receive an order for a given vendor code, you may want to check to make sure the vendor code belongs to the set of vendor codes you handle. In these cases a HashSet<T> is useful for super-quick lookups where order is not important. Once again, like in Dictionary, the type T should have a valid implementation of GetHashCode() and Equals(), or you should provide an appropriate IEqualityComparer<T> to the HashSet<T> on construction. The SortedSet<T> is to HashSet<T> what the SortedDictionary<TKey,TValue> is to Dictionary<TKey,TValue>. That is, the SortedSet<T> is a binary tree where the key and value are the same object. This once again means that adding/removing/lookups are logarithmic - O(log n) - but you gain the ability to iterate over the items in order. For this collection to be effective, type T must implement IComparable<T> or you need to supply an external IComparer<T>. Finally, the Stack<T> and Queue<T> are two very specific collections that allow you to handle a sequential collection of objects in very specific ways. The Stack<T> is a last-in-first-out (LIFO) container where items are added and removed from the top of the stack. Typically this is useful in situations where you want to stack actions and then be able to undo those actions in reverse order as needed. The Queue<T> on the other hand is a first-in-first-out container which adds items at the end of the queue and removes items from the front. This is useful for situations where you need to process items in the order in which they came, such as a print spooler or waiting lines. So that's the basic collections. Let's summarize what we've learned in a quick reference table.  Collection Ordered? Contiguous Storage? Direct Access? Lookup Efficiency Manipulate Efficiency Notes Dictionary No Yes Via Key Key: O(1) O(1) Best for high performance lookups. SortedDictionary Yes No Via Key Key: O(log n) O(log n) Compromise of Dictionary speed and ordering, uses binary search tree. SortedList Yes Yes Via Key Key: O(log n) O(n) Very similar to SortedDictionary, except tree is implemented in an array, so has faster lookup on preloaded data, but slower loads. List No Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no ordering. LinkedList No No No Value: O(n) O(1) Best for lists where inserting/deleting in middle is common and no direct access required. HashSet No Yes Via Key Key: O(1) O(1) Unique unordered collection, like a Dictionary except key and value are same object. SortedSet Yes No Via Key Key: O(log n) O(log n) Unique ordered collection, like SortedDictionary except key and value are same object. Stack No Yes Only Top Top: O(1) O(1)* Essentially same as List<T> except only process as LIFO Queue No Yes Only Front Front: O(1) O(1) Essentially same as List<T> except only process as FIFO   The Original Collections: System.Collections namespace The original collection classes are largely considered deprecated by developers and by Microsoft itself. In fact they indicate that for the most part you should always favor the generic or concurrent collections, and only use the original collections when you are dealing with legacy .NET code. Because these collections are out of vogue, let's just briefly mention the original collection and their generic equivalents: ArrayList A dynamic, contiguous collection of objects. Favor the generic collection List<T> instead. Hashtable Associative, unordered collection of key-value pairs of objects. Favor the generic collection Dictionary<TKey,TValue> instead. Queue First-in-first-out (FIFO) collection of objects. Favor the generic collection Queue<T> instead. SortedList Associative, ordered collection of key-value pairs of objects. Favor the generic collection SortedList<T> instead. Stack Last-in-first-out (LIFO) collection of objects. Favor the generic collection Stack<T> instead. In general, the older collections are non-type-safe and in some cases less performant than their generic counterparts. Once again, the only reason you should fall back on these older collections is for backward compatibility with legacy code and libraries only. The Concurrent Collections: System.Collections.Concurrent namespace The concurrent collections are new as of .NET 4.0 and are included in the System.Collections.Concurrent namespace. These collections are optimized for use in situations where multi-threaded read and write access of a collection is desired. The concurrent queue, stack, and dictionary work much as you'd expect. The bag and blocking collection are more unique. Below is the summary of each with a link to a blog post I did on each of them. ConcurrentQueue Thread-safe version of a queue (FIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentStack Thread-safe version of a stack (LIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentBag Thread-safe unordered collection of objects. Optimized for situations where a thread may be bother reader and writer. For more information see: C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection ConcurrentDictionary Thread-safe version of a dictionary. Optimized for multiple readers (allows multiple readers under same lock). For more information see C#/.NET Little Wonders: The ConcurrentDictionary BlockingCollection Wrapper collection that implement producers & consumers paradigm. Readers can block until items are available to read. Writers can block until space is available to write (if bounded). For more information see C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection Summary The .NET BCL has lots of collections built in to help you store and manipulate collections of data. Understanding how these collections work and knowing in which situations each container is best is one of the key skills necessary to build more performant code. Choosing the wrong collection for the job can make your code much slower or even harder to maintain if you choose one that doesn’t perform as well or otherwise doesn’t exactly fit the situation. Remember to avoid the original collections and stick with the generic collections.  If you need concurrent access, you can use the generic collections if the data is read-only, or consider the concurrent collections for mixed-access if you are running on .NET 4.0 or higher.   Tweet Technorati Tags: C#,.NET,Collecitons,Generic,Concurrent,Dictionary,List,Stack,Queue,SortedList,SortedDictionary,HashSet,SortedSet

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  • SQL Monitor’s data repository

    - by Chris Lambrou
    As one of the developers of SQL Monitor, I often get requests passed on by our support people from customers who are looking to dip into SQL Monitor’s own data repository, in order to pull out bits of information that they’re interested in. Since there’s clearly interest out there in playing around directly with the data repository, I thought I’d write some blog posts to start to describe how it all works. The hardest part for me is knowing where to begin, since the schema of the data repository is pretty big. Hmmm… I guess it’s tricky for anyone to write anything but the most trivial of queries against the data repository without understanding the hierarchy of monitored objects, so perhaps my first post should start there. I always imagine that whenever a customer fires up SSMS and starts to explore their SQL Monitor data repository database, they become immediately bewildered by the schema – that was certainly my experience when I did so for the first time. The following query shows the number of different object types in the data repository schema: SELECT type_desc, COUNT(*) AS [count] FROM sys.objects GROUP BY type_desc ORDER BY type_desc;  type_desccount 1DEFAULT_CONSTRAINT63 2FOREIGN_KEY_CONSTRAINT181 3INTERNAL_TABLE3 4PRIMARY_KEY_CONSTRAINT190 5SERVICE_QUEUE3 6SQL_INLINE_TABLE_VALUED_FUNCTION381 7SQL_SCALAR_FUNCTION2 8SQL_STORED_PROCEDURE100 9SYSTEM_TABLE41 10UNIQUE_CONSTRAINT54 11USER_TABLE193 12VIEW124 With 193 tables, 124 views, 100 stored procedures and 381 table valued functions, that’s quite a hefty schema, and when you browse through it using SSMS, it can be a bit daunting at first. So, where to begin? Well, let’s narrow things down a bit and only look at the tables belonging to the data schema. That’s where all of the collected monitoring data is stored by SQL Monitor. The following query gives us the names of those tables: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' ORDER BY sch.name, obj.name; This query still returns 110 tables. I won’t show them all here, but let’s have a look at the first few of them:  name 1data.Cluster_Keys 2data.Cluster_Machine_ClockSkew_UnstableSamples 3data.Cluster_Machine_Cluster_StableSamples 4data.Cluster_Machine_Keys 5data.Cluster_Machine_LogicalDisk_Capacity_StableSamples 6data.Cluster_Machine_LogicalDisk_Keys 7data.Cluster_Machine_LogicalDisk_Sightings 8data.Cluster_Machine_LogicalDisk_UnstableSamples 9data.Cluster_Machine_LogicalDisk_Volume_StableSamples 10data.Cluster_Machine_Memory_Capacity_StableSamples 11data.Cluster_Machine_Memory_UnstableSamples 12data.Cluster_Machine_Network_Capacity_StableSamples 13data.Cluster_Machine_Network_Keys 14data.Cluster_Machine_Network_Sightings 15data.Cluster_Machine_Network_UnstableSamples 16data.Cluster_Machine_OperatingSystem_StableSamples 17data.Cluster_Machine_Ping_UnstableSamples 18data.Cluster_Machine_Process_Instances 19data.Cluster_Machine_Process_Keys 20data.Cluster_Machine_Process_Owner_Instances 21data.Cluster_Machine_Process_Sightings 22data.Cluster_Machine_Process_UnstableSamples 23… There are two things I want to draw your attention to: The table names describe a hierarchy of the different types of object that are monitored by SQL Monitor (e.g. clusters, machines and disks). For each object type in the hierarchy, there are multiple tables, ending in the suffixes _Keys, _Sightings, _StableSamples and _UnstableSamples. Not every object type has a table for every suffix, but the _Keys suffix is especially important and a _Keys table does indeed exist for every object type. In fact, if we limit the query to return only those tables ending in _Keys, we reveal the full object hierarchy: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' AND obj.name LIKE '%_Keys' ORDER BY sch.name, obj.name;  name 1data.Cluster_Keys 2data.Cluster_Machine_Keys 3data.Cluster_Machine_LogicalDisk_Keys 4data.Cluster_Machine_Network_Keys 5data.Cluster_Machine_Process_Keys 6data.Cluster_Machine_Services_Keys 7data.Cluster_ResourceGroup_Keys 8data.Cluster_ResourceGroup_Resource_Keys 9data.Cluster_SqlServer_Agent_Job_History_Keys 10data.Cluster_SqlServer_Agent_Job_Keys 11data.Cluster_SqlServer_Database_BackupType_Backup_Keys 12data.Cluster_SqlServer_Database_BackupType_Keys 13data.Cluster_SqlServer_Database_CustomMetric_Keys 14data.Cluster_SqlServer_Database_File_Keys 15data.Cluster_SqlServer_Database_Keys 16data.Cluster_SqlServer_Database_Table_Index_Keys 17data.Cluster_SqlServer_Database_Table_Keys 18data.Cluster_SqlServer_Error_Keys 19data.Cluster_SqlServer_Keys 20data.Cluster_SqlServer_Services_Keys 21data.Cluster_SqlServer_SqlProcess_Keys 22data.Cluster_SqlServer_TopQueries_Keys 23data.Cluster_SqlServer_Trace_Keys 24data.Group_Keys The full object type hierarchy looks like this: Cluster Machine LogicalDisk Network Process Services ResourceGroup Resource SqlServer Agent Job History Database BackupType Backup CustomMetric File Table Index Error Services SqlProcess TopQueries Trace Group Okay, but what about the individual objects themselves represented at each level in this hierarchy? Well that’s what the _Keys tables are for. This is probably best illustrated by way of a simple example – how can I query my own data repository to find the databases on my own PC for which monitoring data has been collected? Like this: SELECT clstr._Name AS cluster_name, srvr._Name AS instance_name, db._Name AS database_name FROM data.Cluster_SqlServer_Database_Keys db JOIN data.Cluster_SqlServer_Keys srvr ON db.ParentId = srvr.Id -- Note here how the parent of a Database is a Server JOIN data.Cluster_Keys clstr ON srvr.ParentId = clstr.Id -- Note here how the parent of a Server is a Cluster WHERE clstr._Name = 'dev-chrisl2' -- This is the hostname of my own PC ORDER BY clstr._Name, srvr._Name, db._Name;  cluster_nameinstance_namedatabase_name 1dev-chrisl2SqlMonitorData 2dev-chrisl2master 3dev-chrisl2model 4dev-chrisl2msdb 5dev-chrisl2mssqlsystemresource 6dev-chrisl2tempdb 7dev-chrisl2sql2005SqlMonitorData 8dev-chrisl2sql2005TestDatabase 9dev-chrisl2sql2005master 10dev-chrisl2sql2005model 11dev-chrisl2sql2005msdb 12dev-chrisl2sql2005mssqlsystemresource 13dev-chrisl2sql2005tempdb 14dev-chrisl2sql2008SqlMonitorData 15dev-chrisl2sql2008master 16dev-chrisl2sql2008model 17dev-chrisl2sql2008msdb 18dev-chrisl2sql2008mssqlsystemresource 19dev-chrisl2sql2008tempdb These results show that I have three SQL Server instances on my machine (a default instance, one named sql2005 and one named sql2008), and each instance has the usual set of system databases, along with a database named SqlMonitorData. Basically, this is where I test SQL Monitor on different versions of SQL Server, when I’m developing. There are a few important things we can learn from this query: Each _Keys table has a column named Id. This is the primary key. Each _Keys table has a column named ParentId. A foreign key relationship is defined between each _Keys table and its parent _Keys table in the hierarchy. There are two exceptions to this, Cluster_Keys and Group_Keys, because clusters and groups live at the root level of the object hierarchy. Each _Keys table has a column named _Name. This is used to uniquely identify objects in the table within the scope of the same shared parent object. Actually, that last item isn’t always true. In some cases, the _Name column is actually called something else. For example, the data.Cluster_Machine_Services_Keys table has a column named _ServiceName instead of _Name (sorry for the inconsistency). In other cases, a name isn’t sufficient to uniquely identify an object. For example, right now my PC has multiple processes running, all sharing the same name, Chrome (one for each tab open in my web-browser). In such cases, multiple columns are used to uniquely identify an object within the scope of the same shared parent object. Well, that’s it for now. I’ve given you enough information for you to explore the _Keys tables to see how objects are stored in your own data repositories. In a future post, I’ll try to explain how monitoring data is stored for each object, using the _StableSamples and _UnstableSamples tables. If you have any questions about this post, or suggestions for future posts, just submit them in the comments section below.

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  • HPC Server Dynamic Job Scheduling: when jobs spawn jobs

    - by JoshReuben
    HPC Job Types HPC has 3 types of jobs http://technet.microsoft.com/en-us/library/cc972750(v=ws.10).aspx · Task Flow – vanilla sequence · Parametric Sweep – concurrently run multiple instances of the same program, each with a different work unit input · MPI – message passing between master & slave tasks But when you try go outside the box – job tasks that spawn jobs, blocking the parent task – you run the risk of resource starvation, deadlocks, and recursive, non-converging or exponential blow-up. The solution to this is to write some performance monitoring and job scheduling code. You can do this in 2 ways: manually control scheduling - allocate/ de-allocate resources, change job priorities, pause & resume tasks , restrict long running tasks to specific compute clusters Semi-automatically - set threshold params for scheduling. How – Control Job Scheduling In order to manage the tasks and resources that are associated with a job, you will need to access the ISchedulerJob interface - http://msdn.microsoft.com/en-us/library/microsoft.hpc.scheduler.ischedulerjob_members(v=vs.85).aspx This really allows you to control how a job is run – you can access & tweak the following features: max / min resource values whether job resources can grow / shrink, and whether jobs can be pre-empted, whether the job is exclusive per node the creator process id & the job pool timestamp of job creation & completion job priority, hold time & run time limit Re-queue count Job progress Max/ min Number of cores, nodes, sockets, RAM Dynamic task list – can add / cancel jobs on the fly Job counters When – poll perf counters Tweaking the job scheduler should be done on the basis of resource utilization according to PerfMon counters – HPC exposes 2 Perf objects: Compute Clusters, Compute Nodes http://technet.microsoft.com/en-us/library/cc720058(v=ws.10).aspx You can monitor running jobs according to dynamic thresholds – use your own discretion: Percentage processor time Number of running jobs Number of running tasks Total number of processors Number of processors in use Number of processors idle Number of serial tasks Number of parallel tasks Design Your algorithms correctly Finally , don’t assume you have unlimited compute resources in your cluster – design your algorithms with the following factors in mind: · Branching factor - http://en.wikipedia.org/wiki/Branching_factor - dynamically optimize the number of children per node · cutoffs to prevent explosions - http://en.wikipedia.org/wiki/Limit_of_a_sequence - not all functions converge after n attempts. You also need a threshold of good enough, diminishing returns · heuristic shortcuts - http://en.wikipedia.org/wiki/Heuristic - sometimes an exhaustive search is impractical and short cuts are suitable · Pruning http://en.wikipedia.org/wiki/Pruning_(algorithm) – remove / de-prioritize unnecessary tree branches · avoid local minima / maxima - http://en.wikipedia.org/wiki/Local_minima - sometimes an algorithm cant converge because it gets stuck in a local saddle – try simulated annealing, hill climbing or genetic algorithms to get out of these ruts   watch out for rounding errors – http://en.wikipedia.org/wiki/Round-off_error - multiple iterations can in parallel can quickly amplify & blow up your algo ! Use an epsilon, avoid floating point errors,  truncations, approximations Happy Coding !

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