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  • List goals/targets in GNU make

    - by BitShifter
    I have a fairly large makefile that creates a number of targets on the fly by computing names from variables. (eg foo$(VAR) : $(PREREQS)). Is there any way that gnu make can be convinced to spit out a list of targets after it has expanded these variables?

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  • When is the onPreExecute called on an AsyncTask running parallely or concurrently?

    - by Debarshi Dutta
    I am using Android HoneyComb.I need to execute some tasks parallely and I am using AsyncTask's public final AsyncTask executeOnExecutor (Executor exec, Params... params) method.In each separate thread I am computing some values and I need to store then in an ArrayList.I must then sort all the values in the arrayList and then display it in the UI.Now my question is if one of the thread gets completed earlier than the other then will it immediately call the onPostExecute method or onPostExecute method will be called after all the background threads have been completed?MY program implementation depends on what occurs here.

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  • How do you raise a Java BigInteger to the power of a BigInteger without doing modular arithmetic?

    - by angstrom91
    I'm doing some large integer computing, and I need to raise a BigInteger to the power of another BigInteger. The .pow() method does what I want, but takes an int value as an argument. The .modPow method takes a BigInteger as an argument, but I do not want an answer congruent to the value I'm trying to compute. My BigInteger exponent is too large to be represented as an int, can someone suggest a way to work around this limitation?

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  • Jave JIT compiler compiles at compile time or runtime ?

    - by Tony
    From wiki: In computing, just-in-time compilation (JIT), also known as dynamic translation, is a technique for improving the runtime performance of a computer program. So I guess JVM has another compiler, not javac, that only compiles bytecode to machine code at runtime, while javac compiles sources to bytecode,is that right?

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  • Wrong root on image_tag

    - by Euwyn
    On my dev setup, the image_tag is mysteriously pointing to my public www server (i.e. computing the image path as http://www.domain.com/images/blah.jpg). Where is this option set?

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  • Windows Azure: Parallelization of the code

    - by veda
    I have some matrix multiplication operation. I want to parallelize the execution of those operations through multiple processors.. This can be done on high performance computing cluster using MPI (Message Passing Interface). Like wise, can I do some parallelization in the cloud using multiple worker roles. Is there any means for doing that.

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  • Is possible to generate constant value during compilation?

    - by AOI Karasu
    I would like my classes to be identified each type by an unique hash code. But I don't want these hashed to be generated every time a method, eg. int GetHashCode(), is invoked during runtime. I'd like to use already generated constants and I was hoping there is a way to make the compiler do some come computing and set these constants. Can it be done using templates? Could you give me some example, if it is possible.

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  • Getting up to speed on modern architecture

    - by Matt Thrower
    Hi, I don't have any formal qualifications in computer science, rather I taught myself classic ASP back in the days of the dotcom boom and managed to get myself a job and my career developed from there. I was a confident and, I think, pretty good programmer in ASP 3 but as others have observed one of the problems with classic ASP was that it did a very good job of hiding the nitty-gritty of http so you could become quite competent as a programmer on the basis of relatively poor understanding of the technology you were working with. When I changed on to .NET at first I treated it like classic ASP, developing stand-alone applications as individual websites simply because I didn't know any better at the time. I moved jobs at this point and spent the next several years working on a single site whose architecture relied heavily on custom objects: in other words I gained a lot of experience working with .NET as a middle-tier development tool using a quite old-fashioned approach to OO design along the lines of the classic "car" class example that's so often used to teach OO. Breaking down programs into blocks of functionality and basing your classes and methods around that. Although we worked under an Agile approach to manage the work the whole setup was classic client/server stuff. That suited me and I gradually got to grips with .NET and started using it far more in the manner that it should be, and I began to see the power inherent in the technology and precisely why it was so much better than good old ASP 3. In my latest job I have found myself suddenly dropped in at the deep end with two quite young, skilled and very cutting-edge programmers. They've built a site architecture which is modelling along a lot of stuff which is new to me and which, in truth I'm having a lot of trouble understanding. The application is built on a cloud computing model with multi-tenancy and the architecture is all loosely coupled using a lot of interfaces, factories and the like. They use nHibernate a lot too. Shortly after I joined, both these guys left and I'm now supposedly the senior developer on a system whose technology and architecture I don't really understand and I have no-one to ask questions of. Except you, the internet. Frankly I feel like I've been pitched in at the deep end and I'm sinking. I'm not sure if this is because I lack the educational background to understand this stuff, if I'm simply not mathematically minded enough for modern computing (my maths was never great - my approach to design is often to simply debug until it works, then refactor until it looks neat), or whether I've simply been presented with too much of too radical a nature at once. But the only way to find out which it is is to try and learn it. So can anyone suggest some good places to start? Good books, tutorials or blogs? I've found a lot of internet material simply presupposes a level of understanding that I just don't have. Your advice is much appreciated. Help a middle-aged, stuck in the mud developer get enthusastic again! Please!

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  • Pi/Infinite Numbers

    - by Ben Shelock
    I'm curious about infinite numbers in computing, in particular pi. For a computer to render a circle it would have to understand pi. But how can it if it is infinite? Am I looking too much into this? Would it just use a rounded value?

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  • Java JIT compiler compiles at compile time or runtime ?

    - by Tony
    From wiki: In computing, just-in-time compilation (JIT), also known as dynamic translation, is a technique for improving the runtime performance of a computer program. So I guess JVM has another compiler, not javac, that only compiles bytecode to machine code at runtime, while javac compiles sources to bytecode,is that right?

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  • take performance as the only criterion for a smal site, which framework should I choose on a shared

    - by john
    Dear friends, I'm trying to set up a small full functional website for a small community on a shared hosting. Scientific computing is quite heavy. Scalability is not important. The only criterion is performance. Which framework would you suggest among the following:(or more) from your list) 1)Ruby on Rails 2) Grails 3) asp.net 4) zend I'm really new to this area, only starting reading some books and googling different blogs...so your expertise is really appreciated! thanks!

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  • C++ Expression Templates

    - by yCalleecharan
    Hi, I currently use C for numerical computations. I've heard that using C++ Expression Templates is better for scientific computing. What are C++ Expression Templates in simple terms? Are there books around that discuss numerical methods/computations using C++ Expression Templates? In what way, C++ Expression Templates are better than using pure C? Thanks a lot

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  • Possible to distribute or parallel process a sequential program?

    - by damigu
    In C++, I've written a mathematical program (for diffusion limited aggregation) where each new point calculated is dependent on all of the preceding points. Is it possible to have such a program work in a parallel or distributed manner to increase computing speed? If so, what type of modifications to the code would I need to look into?

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  • What's the purpose of the rotate instructions (ROL, RCL on x86) ?

    - by lgratian
    I always wondered what's the purpose of the rotate instructions some CPUs have (ROL, RCL on x86, for example). What kind of software makes use of these instructions? I first thought they may be used for encryption/computing hash codes, but these libraries are written usually in C, which doesn't have operators that map to these instructions. Has anybody found an use for them? Why where they added to the instructions set?

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  • C++ variable alias - what's that exactly, and why is it better to turn if off?

    - by Poni
    I've read the essay Surviving the Release Version. Under the "Aliasing bugs" clause it says: You can get tighter code if you tell the compiler that it can assume no aliasing.... I've also read Aliasing (computing). What exactly is a variable alias? I understand it means using a pointer to a variable is an alias, but, how/why does it affect badly, or in other words - why telling the compiler that it can assume no aliasing would get me a "tighter code"

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  • Good resource for studying Database High Availability techniques

    - by Invincible
    Hello Can anybody suggest some good resource/book on Database high availability techniques? Moreover, High-availability of system software like Intrusion Prevention system or Web servers. I am considering high-availability is global term which covers clustring, cloud computing, replication, replica management, distributed synchronization for cluster. Thanks in advance!

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  • Is it faster to compute values in a query, call a Scalar Function (decimal(28,2) datatype) 4 times,

    - by Pulsehead
    I have a handful of queries I need to write in SQL Server 2005. Each Query will be calculating 4 unit cost values based on a handful of (up to 11) fields. Any time I want 1 of these 4 unit cost values, I'll want all 4. Which is quicker? Computing in the SQL Query ((a+b+c+d+e+f+g+h+i)/(j+k)), calling ComputeScalarUnitCost(datapoint.ID) 4 times, or joining to ComputeUnitCostTable(datapoint.ID) one time?

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  • value types in the vm

    - by john.rose
    value types in the vm p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} p.p2 {margin: 0.0px 0.0px 14.0px 0.0px; font: 14.0px Times} p.p3 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times} p.p4 {margin: 0.0px 0.0px 15.0px 0.0px; font: 14.0px Times} p.p5 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier} p.p6 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier; min-height: 17.0px} p.p7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p8 {margin: 0.0px 0.0px 0.0px 36.0px; text-indent: -36.0px; font: 14.0px Times; min-height: 18.0px} p.p9 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p10 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; color: #000000} li.li1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} li.li7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} span.s1 {font: 14.0px Courier} span.s2 {color: #000000} span.s3 {font: 14.0px Courier; color: #000000} ol.ol1 {list-style-type: decimal} Or, enduring values for a changing world. Introduction A value type is a data type which, generally speaking, is designed for being passed by value in and out of methods, and stored by value in data structures. The only value types which the Java language directly supports are the eight primitive types. Java indirectly and approximately supports value types, if they are implemented in terms of classes. For example, both Integer and String may be viewed as value types, especially if their usage is restricted to avoid operations appropriate to Object. In this note, we propose a definition of value types in terms of a design pattern for Java classes, accompanied by a set of usage restrictions. We also sketch the relation of such value types to tuple types (which are a JVM-level notion), and point out JVM optimizations that can apply to value types. This note is a thought experiment to extend the JVM’s performance model in support of value types. The demonstration has two phases.  Initially the extension can simply use design patterns, within the current bytecode architecture, and in today’s Java language. But if the performance model is to be realized in practice, it will probably require new JVM bytecode features, changes to the Java language, or both.  We will look at a few possibilities for these new features. An Axiom of Value In the context of the JVM, a value type is a data type equipped with construction, assignment, and equality operations, and a set of typed components, such that, whenever two variables of the value type produce equal corresponding values for their components, the values of the two variables cannot be distinguished by any JVM operation. Here are some corollaries: A value type is immutable, since otherwise a copy could be constructed and the original could be modified in one of its components, allowing the copies to be distinguished. Changing the component of a value type requires construction of a new value. The equals and hashCode operations are strictly component-wise. If a value type is represented by a JVM reference, that reference cannot be successfully synchronized on, and cannot be usefully compared for reference equality. A value type can be viewed in terms of what it doesn’t do. We can say that a value type omits all value-unsafe operations, which could violate the constraints on value types.  These operations, which are ordinarily allowed for Java object types, are pointer equality comparison (the acmp instruction), synchronization (the monitor instructions), all the wait and notify methods of class Object, and non-trivial finalize methods. The clone method is also value-unsafe, although for value types it could be treated as the identity function. Finally, and most importantly, any side effect on an object (however visible) also counts as an value-unsafe operation. A value type may have methods, but such methods must not change the components of the value. It is reasonable and useful to define methods like toString, equals, and hashCode on value types, and also methods which are specifically valuable to users of the value type. Representations of Value Value types have two natural representations in the JVM, unboxed and boxed. An unboxed value consists of the components, as simple variables. For example, the complex number x=(1+2i), in rectangular coordinate form, may be represented in unboxed form by the following pair of variables: /*Complex x = Complex.valueOf(1.0, 2.0):*/ double x_re = 1.0, x_im = 2.0; These variables might be locals, parameters, or fields. Their association as components of a single value is not defined to the JVM. Here is a sample computation which computes the norm of the difference between two complex numbers: double distance(/*Complex x:*/ double x_re, double x_im,         /*Complex y:*/ double y_re, double y_im) {     /*Complex z = x.minus(y):*/     double z_re = x_re - y_re, z_im = x_im - y_im;     /*return z.abs():*/     return Math.sqrt(z_re*z_re + z_im*z_im); } A boxed representation groups component values under a single object reference. The reference is to a ‘wrapper class’ that carries the component values in its fields. (A primitive type can naturally be equated with a trivial value type with just one component of that type. In that view, the wrapper class Integer can serve as a boxed representation of value type int.) The unboxed representation of complex numbers is practical for many uses, but it fails to cover several major use cases: return values, array elements, and generic APIs. The two components of a complex number cannot be directly returned from a Java function, since Java does not support multiple return values. The same story applies to array elements: Java has no ’array of structs’ feature. (Double-length arrays are a possible workaround for complex numbers, but not for value types with heterogeneous components.) By generic APIs I mean both those which use generic types, like Arrays.asList and those which have special case support for primitive types, like String.valueOf and PrintStream.println. Those APIs do not support unboxed values, and offer some problems to boxed values. Any ’real’ JVM type should have a story for returns, arrays, and API interoperability. The basic problem here is that value types fall between primitive types and object types. Value types are clearly more complex than primitive types, and object types are slightly too complicated. Objects are a little bit dangerous to use as value carriers, since object references can be compared for pointer equality, and can be synchronized on. Also, as many Java programmers have observed, there is often a performance cost to using wrapper objects, even on modern JVMs. Even so, wrapper classes are a good starting point for talking about value types. If there were a set of structural rules and restrictions which would prevent value-unsafe operations on value types, wrapper classes would provide a good notation for defining value types. This note attempts to define such rules and restrictions. Let’s Start Coding Now it is time to look at some real code. Here is a definition, written in Java, of a complex number value type. @ValueSafe public final class Complex implements java.io.Serializable {     // immutable component structure:     public final double re, im;     private Complex(double re, double im) {         this.re = re; this.im = im;     }     // interoperability methods:     public String toString() { return "Complex("+re+","+im+")"; }     public List<Double> asList() { return Arrays.asList(re, im); }     public boolean equals(Complex c) {         return re == c.re && im == c.im;     }     public boolean equals(@ValueSafe Object x) {         return x instanceof Complex && equals((Complex) x);     }     public int hashCode() {         return 31*Double.valueOf(re).hashCode()                 + Double.valueOf(im).hashCode();     }     // factory methods:     public static Complex valueOf(double re, double im) {         return new Complex(re, im);     }     public Complex changeRe(double re2) { return valueOf(re2, im); }     public Complex changeIm(double im2) { return valueOf(re, im2); }     public static Complex cast(@ValueSafe Object x) {         return x == null ? ZERO : (Complex) x;     }     // utility methods and constants:     public Complex plus(Complex c)  { return new Complex(re+c.re, im+c.im); }     public Complex minus(Complex c) { return new Complex(re-c.re, im-c.im); }     public double abs() { return Math.sqrt(re*re + im*im); }     public static final Complex PI = valueOf(Math.PI, 0.0);     public static final Complex ZERO = valueOf(0.0, 0.0); } This is not a minimal definition, because it includes some utility methods and other optional parts.  The essential elements are as follows: The class is marked as a value type with an annotation. The class is final, because it does not make sense to create subclasses of value types. The fields of the class are all non-private and final.  (I.e., the type is immutable and structurally transparent.) From the supertype Object, all public non-final methods are overridden. The constructor is private. Beyond these bare essentials, we can observe the following features in this example, which are likely to be typical of all value types: One or more factory methods are responsible for value creation, including a component-wise valueOf method. There are utility methods for complex arithmetic and instance creation, such as plus and changeIm. There are static utility constants, such as PI. The type is serializable, using the default mechanisms. There are methods for converting to and from dynamically typed references, such as asList and cast. The Rules In order to use value types properly, the programmer must avoid value-unsafe operations.  A helpful Java compiler should issue errors (or at least warnings) for code which provably applies value-unsafe operations, and should issue warnings for code which might be correct but does not provably avoid value-unsafe operations.  No such compilers exist today, but to simplify our account here, we will pretend that they do exist. A value-safe type is any class, interface, or type parameter marked with the @ValueSafe annotation, or any subtype of a value-safe type.  If a value-safe class is marked final, it is in fact a value type.  All other value-safe classes must be abstract.  The non-static fields of a value class must be non-public and final, and all its constructors must be private. Under the above rules, a standard interface could be helpful to define value types like Complex.  Here is an example: @ValueSafe public interface ValueType extends java.io.Serializable {     // All methods listed here must get redefined.     // Definitions must be value-safe, which means     // they may depend on component values only.     List<? extends Object> asList();     int hashCode();     boolean equals(@ValueSafe Object c);     String toString(); } //@ValueSafe inherited from supertype: public final class Complex implements ValueType { … The main advantage of such a conventional interface is that (unlike an annotation) it is reified in the runtime type system.  It could appear as an element type or parameter bound, for facilities which are designed to work on value types only.  More broadly, it might assist the JVM to perform dynamic enforcement of the rules for value types. Besides types, the annotation @ValueSafe can mark fields, parameters, local variables, and methods.  (This is redundant when the type is also value-safe, but may be useful when the type is Object or another supertype of a value type.)  Working forward from these annotations, an expression E is defined as value-safe if it satisfies one or more of the following: The type of E is a value-safe type. E names a field, parameter, or local variable whose declaration is marked @ValueSafe. E is a call to a method whose declaration is marked @ValueSafe. E is an assignment to a value-safe variable, field reference, or array reference. E is a cast to a value-safe type from a value-safe expression. E is a conditional expression E0 ? E1 : E2, and both E1 and E2 are value-safe. Assignments to value-safe expressions and initializations of value-safe names must take their values from value-safe expressions. A value-safe expression may not be the subject of a value-unsafe operation.  In particular, it cannot be synchronized on, nor can it be compared with the “==” operator, not even with a null or with another value-safe type. In a program where all of these rules are followed, no value-type value will be subject to a value-unsafe operation.  Thus, the prime axiom of value types will be satisfied, that no two value type will be distinguishable as long as their component values are equal. More Code To illustrate these rules, here are some usage examples for Complex: Complex pi = Complex.valueOf(Math.PI, 0); Complex zero = pi.changeRe(0);  //zero = pi; zero.re = 0; ValueType vtype = pi; @SuppressWarnings("value-unsafe")   Object obj = pi; @ValueSafe Object obj2 = pi; obj2 = new Object();  // ok List<Complex> clist = new ArrayList<Complex>(); clist.add(pi);  // (ok assuming List.add param is @ValueSafe) List<ValueType> vlist = new ArrayList<ValueType>(); vlist.add(pi);  // (ok) List<Object> olist = new ArrayList<Object>(); olist.add(pi);  // warning: "value-unsafe" boolean z = pi.equals(zero); boolean z1 = (pi == zero);  // error: reference comparison on value type boolean z2 = (pi == null);  // error: reference comparison on value type boolean z3 = (pi == obj2);  // error: reference comparison on value type synchronized (pi) { }  // error: synch of value, unpredictable result synchronized (obj2) { }  // unpredictable result Complex qq = pi; qq = null;  // possible NPE; warning: “null-unsafe" qq = (Complex) obj;  // warning: “null-unsafe" qq = Complex.cast(obj);  // OK @SuppressWarnings("null-unsafe")   Complex empty = null;  // possible NPE qq = empty;  // possible NPE (null pollution) The Payoffs It follows from this that either the JVM or the java compiler can replace boxed value-type values with unboxed ones, without affecting normal computations.  Fields and variables of value types can be split into their unboxed components.  Non-static methods on value types can be transformed into static methods which take the components as value parameters. Some common questions arise around this point in any discussion of value types. Why burden the programmer with all these extra rules?  Why not detect programs automagically and perform unboxing transparently?  The answer is that it is easy to break the rules accidently unless they are agreed to by the programmer and enforced.  Automatic unboxing optimizations are tantalizing but (so far) unreachable ideal.  In the current state of the art, it is possible exhibit benchmarks in which automatic unboxing provides the desired effects, but it is not possible to provide a JVM with a performance model that assures the programmer when unboxing will occur.  This is why I’m writing this note, to enlist help from, and provide assurances to, the programmer.  Basically, I’m shooting for a good set of user-supplied “pragmas” to frame the desired optimization. Again, the important thing is that the unboxing must be done reliably, or else programmers will have no reason to work with the extra complexity of the value-safety rules.  There must be a reasonably stable performance model, wherein using a value type has approximately the same performance characteristics as writing the unboxed components as separate Java variables. There are some rough corners to the present scheme.  Since Java fields and array elements are initialized to null, value-type computations which incorporate uninitialized variables can produce null pointer exceptions.  One workaround for this is to require such variables to be null-tested, and the result replaced with a suitable all-zero value of the value type.  That is what the “cast” method does above. Generically typed APIs like List<T> will continue to manipulate boxed values always, at least until we figure out how to do reification of generic type instances.  Use of such APIs will elicit warnings until their type parameters (and/or relevant members) are annotated or typed as value-safe.  Retrofitting List<T> is likely to expose flaws in the present scheme, which we will need to engineer around.  Here are a couple of first approaches: public interface java.util.List<@ValueSafe T> extends Collection<T> { … public interface java.util.List<T extends Object|ValueType> extends Collection<T> { … (The second approach would require disjunctive types, in which value-safety is “contagious” from the constituent types.) With more transformations, the return value types of methods can also be unboxed.  This may require significant bytecode-level transformations, and would work best in the presence of a bytecode representation for multiple value groups, which I have proposed elsewhere under the title “Tuples in the VM”. But for starters, the JVM can apply this transformation under the covers, to internally compiled methods.  This would give a way to express multiple return values and structured return values, which is a significant pain-point for Java programmers, especially those who work with low-level structure types favored by modern vector and graphics processors.  The lack of multiple return values has a strong distorting effect on many Java APIs. Even if the JVM fails to unbox a value, there is still potential benefit to the value type.  Clustered computing systems something have copy operations (serialization or something similar) which apply implicitly to command operands.  When copying JVM objects, it is extremely helpful to know when an object’s identity is important or not.  If an object reference is a copied operand, the system may have to create a proxy handle which points back to the original object, so that side effects are visible.  Proxies must be managed carefully, and this can be expensive.  On the other hand, value types are exactly those types which a JVM can “copy and forget” with no downside. Array types are crucial to bulk data interfaces.  (As data sizes and rates increase, bulk data becomes more important than scalar data, so arrays are definitely accompanying us into the future of computing.)  Value types are very helpful for adding structure to bulk data, so a successful value type mechanism will make it easier for us to express richer forms of bulk data. Unboxing arrays (i.e., arrays containing unboxed values) will provide better cache and memory density, and more direct data movement within clustered or heterogeneous computing systems.  They require the deepest transformations, relative to today’s JVM.  There is an impedance mismatch between value-type arrays and Java’s covariant array typing, so compromises will need to be struck with existing Java semantics.  It is probably worth the effort, since arrays of unboxed value types are inherently more memory-efficient than standard Java arrays, which rely on dependent pointer chains. It may be sufficient to extend the “value-safe” concept to array declarations, and allow low-level transformations to change value-safe array declarations from the standard boxed form into an unboxed tuple-based form.  Such value-safe arrays would not be convertible to Object[] arrays.  Certain connection points, such as Arrays.copyOf and System.arraycopy might need additional input/output combinations, to allow smooth conversion between arrays with boxed and unboxed elements. Alternatively, the correct solution may have to wait until we have enough reification of generic types, and enough operator overloading, to enable an overhaul of Java arrays. Implicit Method Definitions The example of class Complex above may be unattractively complex.  I believe most or all of the elements of the example class are required by the logic of value types. If this is true, a programmer who writes a value type will have to write lots of error-prone boilerplate code.  On the other hand, I think nearly all of the code (except for the domain-specific parts like plus and minus) can be implicitly generated. Java has a rule for implicitly defining a class’s constructor, if no it defines no constructors explicitly.  Likewise, there are rules for providing default access modifiers for interface members.  Because of the highly regular structure of value types, it might be reasonable to perform similar implicit transformations on value types.  Here’s an example of a “highly implicit” definition of a complex number type: public class Complex implements ValueType {  // implicitly final     public double re, im;  // implicitly public final     //implicit methods are defined elementwise from te fields:     //  toString, asList, equals(2), hashCode, valueOf, cast     //optionally, explicit methods (plus, abs, etc.) would go here } In other words, with the right defaults, a simple value type definition can be a one-liner.  The observant reader will have noticed the similarities (and suitable differences) between the explicit methods above and the corresponding methods for List<T>. Another way to abbreviate such a class would be to make an annotation the primary trigger of the functionality, and to add the interface(s) implicitly: public @ValueType class Complex { … // implicitly final, implements ValueType (But to me it seems better to communicate the “magic” via an interface, even if it is rooted in an annotation.) Implicitly Defined Value Types So far we have been working with nominal value types, which is to say that the sequence of typed components is associated with a name and additional methods that convey the intention of the programmer.  A simple ordered pair of floating point numbers can be variously interpreted as (to name a few possibilities) a rectangular or polar complex number or Cartesian point.  The name and the methods convey the intended meaning. But what if we need a truly simple ordered pair of floating point numbers, without any further conceptual baggage?  Perhaps we are writing a method (like “divideAndRemainder”) which naturally returns a pair of numbers instead of a single number.  Wrapping the pair of numbers in a nominal type (like “QuotientAndRemainder”) makes as little sense as wrapping a single return value in a nominal type (like “Quotient”).  What we need here are structural value types commonly known as tuples. For the present discussion, let us assign a conventional, JVM-friendly name to tuples, roughly as follows: public class java.lang.tuple.$DD extends java.lang.tuple.Tuple {      double $1, $2; } Here the component names are fixed and all the required methods are defined implicitly.  The supertype is an abstract class which has suitable shared declarations.  The name itself mentions a JVM-style method parameter descriptor, which may be “cracked” to determine the number and types of the component fields. The odd thing about such a tuple type (and structural types in general) is it must be instantiated lazily, in response to linkage requests from one or more classes that need it.  The JVM and/or its class loaders must be prepared to spin a tuple type on demand, given a simple name reference, $xyz, where the xyz is cracked into a series of component types.  (Specifics of naming and name mangling need some tasteful engineering.) Tuples also seem to demand, even more than nominal types, some support from the language.  (This is probably because notations for non-nominal types work best as combinations of punctuation and type names, rather than named constructors like Function3 or Tuple2.)  At a minimum, languages with tuples usually (I think) have some sort of simple bracket notation for creating tuples, and a corresponding pattern-matching syntax (or “destructuring bind”) for taking tuples apart, at least when they are parameter lists.  Designing such a syntax is no simple thing, because it ought to play well with nominal value types, and also with pre-existing Java features, such as method parameter lists, implicit conversions, generic types, and reflection.  That is a task for another day. Other Use Cases Besides complex numbers and simple tuples there are many use cases for value types.  Many tuple-like types have natural value-type representations. These include rational numbers, point locations and pixel colors, and various kinds of dates and addresses. Other types have a variable-length ‘tail’ of internal values. The most common example of this is String, which is (mathematically) a sequence of UTF-16 character values. Similarly, bit vectors, multiple-precision numbers, and polynomials are composed of sequences of values. Such types include, in their representation, a reference to a variable-sized data structure (often an array) which (somehow) represents the sequence of values. The value type may also include ’header’ information. Variable-sized values often have a length distribution which favors short lengths. In that case, the design of the value type can make the first few values in the sequence be direct ’header’ fields of the value type. In the common case where the header is enough to represent the whole value, the tail can be a shared null value, or even just a null reference. Note that the tail need not be an immutable object, as long as the header type encapsulates it well enough. This is the case with String, where the tail is a mutable (but never mutated) character array. Field types and their order must be a globally visible part of the API.  The structure of the value type must be transparent enough to have a globally consistent unboxed representation, so that all callers and callees agree about the type and order of components  that appear as parameters, return types, and array elements.  This is a trade-off between efficiency and encapsulation, which is forced on us when we remove an indirection enjoyed by boxed representations.  A JVM-only transformation would not care about such visibility, but a bytecode transformation would need to take care that (say) the components of complex numbers would not get swapped after a redefinition of Complex and a partial recompile.  Perhaps constant pool references to value types need to declare the field order as assumed by each API user. This brings up the delicate status of private fields in a value type.  It must always be possible to load, store, and copy value types as coordinated groups, and the JVM performs those movements by moving individual scalar values between locals and stack.  If a component field is not public, what is to prevent hostile code from plucking it out of the tuple using a rogue aload or astore instruction?  Nothing but the verifier, so we may need to give it more smarts, so that it treats value types as inseparable groups of stack slots or locals (something like long or double). My initial thought was to make the fields always public, which would make the security problem moot.  But public is not always the right answer; consider the case of String, where the underlying mutable character array must be encapsulated to prevent security holes.  I believe we can win back both sides of the tradeoff, by training the verifier never to split up the components in an unboxed value.  Just as the verifier encapsulates the two halves of a 64-bit primitive, it can encapsulate the the header and body of an unboxed String, so that no code other than that of class String itself can take apart the values. Similar to String, we could build an efficient multi-precision decimal type along these lines: public final class DecimalValue extends ValueType {     protected final long header;     protected private final BigInteger digits;     public DecimalValue valueOf(int value, int scale) {         assert(scale >= 0);         return new DecimalValue(((long)value << 32) + scale, null);     }     public DecimalValue valueOf(long value, int scale) {         if (value == (int) value)             return valueOf((int)value, scale);         return new DecimalValue(-scale, new BigInteger(value));     } } Values of this type would be passed between methods as two machine words. Small values (those with a significand which fits into 32 bits) would be represented without any heap data at all, unless the DecimalValue itself were boxed. (Note the tension between encapsulation and unboxing in this case.  It would be better if the header and digits fields were private, but depending on where the unboxing information must “leak”, it is probably safer to make a public revelation of the internal structure.) Note that, although an array of Complex can be faked with a double-length array of double, there is no easy way to fake an array of unboxed DecimalValues.  (Either an array of boxed values or a transposed pair of homogeneous arrays would be reasonable fallbacks, in a current JVM.)  Getting the full benefit of unboxing and arrays will require some new JVM magic. Although the JVM emphasizes portability, system dependent code will benefit from using machine-level types larger than 64 bits.  For example, the back end of a linear algebra package might benefit from value types like Float4 which map to stock vector types.  This is probably only worthwhile if the unboxing arrays can be packed with such values. More Daydreams A more finely-divided design for dynamic enforcement of value safety could feature separate marker interfaces for each invariant.  An empty marker interface Unsynchronizable could cause suitable exceptions for monitor instructions on objects in marked classes.  More radically, a Interchangeable marker interface could cause JVM primitives that are sensitive to object identity to raise exceptions; the strangest result would be that the acmp instruction would have to be specified as raising an exception. @ValueSafe public interface ValueType extends java.io.Serializable,         Unsynchronizable, Interchangeable { … public class Complex implements ValueType {     // inherits Serializable, Unsynchronizable, Interchangeable, @ValueSafe     … It seems possible that Integer and the other wrapper types could be retro-fitted as value-safe types.  This is a major change, since wrapper objects would be unsynchronizable and their references interchangeable.  It is likely that code which violates value-safety for wrapper types exists but is uncommon.  It is less plausible to retro-fit String, since the prominent operation String.intern is often used with value-unsafe code. We should also reconsider the distinction between boxed and unboxed values in code.  The design presented above obscures that distinction.  As another thought experiment, we could imagine making a first class distinction in the type system between boxed and unboxed representations.  Since only primitive types are named with a lower-case initial letter, we could define that the capitalized version of a value type name always refers to the boxed representation, while the initial lower-case variant always refers to boxed.  For example: complex pi = complex.valueOf(Math.PI, 0); Complex boxPi = pi;  // convert to boxed myList.add(boxPi); complex z = myList.get(0);  // unbox Such a convention could perhaps absorb the current difference between int and Integer, double and Double. It might also allow the programmer to express a helpful distinction among array types. As said above, array types are crucial to bulk data interfaces, but are limited in the JVM.  Extending arrays beyond the present limitations is worth thinking about; for example, the Maxine JVM implementation has a hybrid object/array type.  Something like this which can also accommodate value type components seems worthwhile.  On the other hand, does it make sense for value types to contain short arrays?  And why should random-access arrays be the end of our design process, when bulk data is often sequentially accessed, and it might make sense to have heterogeneous streams of data as the natural “jumbo” data structure.  These considerations must wait for another day and another note. More Work It seems to me that a good sequence for introducing such value types would be as follows: Add the value-safety restrictions to an experimental version of javac. Code some sample applications with value types, including Complex and DecimalValue. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. A staggered roll-out like this would decouple language changes from bytecode changes, which is always a convenient thing. A similar investigation should be applied (concurrently) to array types.  In this case, it seems to me that the starting point is in the JVM: Add an experimental unboxing array data structure to a production JVM, perhaps along the lines of Maxine hybrids.  No bytecode or language support is required at first; everything can be done with encapsulated unsafe operations and/or method handles. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. That’s enough musing me for now.  Back to work!

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  • 202 blog articles

    - by mprove
    All my blog articles under blogs.oracle.com since August 2005: 202 blog articles Apr 2012 blogs.oracle.com design patch Mar 2012 Interaction 12 - Critique Mar 2012 Typing. Clicking. Dancing. Feb 2012 Desktop Mobility in Hospitals with Oracle VDI /video Feb 2012 Interaction 12 in Dublin - Highlights of Day 3 Feb 2012 Interaction 12 in Dublin - Highlights of Day 2 Feb 2012 Interaction 12 in Dublin - Highlights of Day 1 Feb 2012 Shit Interaction Designers Say Feb 2012 Tips'n'Tricks for WebCenter #3: How to display custom page titles in Spaces Jan 2012 Tips'n'Tricks for WebCenter #2: How to create an Admin menu in Spaces and save a lot of time Jan 2012 Tips'n'Tricks for WebCenter #1: How to apply custom resources in Spaces Jan 2012 Merry XMas and a Happy 2012! Dec 2011 One Year Oracle SocialChat - The Movie Nov 2011 Frank Ludolph's Last Working Day Nov 2011 Hans Rosling at TED Oct 2011 200 Countries x 200 Years Oct 2011 Blog Aggregation for Desktop Virtualization Oct 2011 Oracle VDI at OOW 2011 Sep 2011 Design for Conversations & Conversations for Design Sep 2011 All Oracle UX Blogs Aug 2011 Farewell Loriot Aug 2011 Oracle VDI 3.3 Overview Aug 2011 Sutherland's Closing Remarks at HyperKult Aug 2011 Surface and Subface Aug 2011 Back to Childhood in UI Design Jul 2011 The Art of Engineering and The Engineering of Art Jul 2011 Oracle VDI Seminar - June-30 Jun 2011 SGD White Paper May 2011 TEDxHamburg Live Feed May 2011 Oracle VDI in 3 Minutes May 2011 Space Ship Earth 2011 May 2011 blog moving times Apr 2011 Frozen tag cloud Apr 2011 Oracle: Hardware Software Complete in 1953 Apr 2011 Interaction Design with Wireframes Apr 2011 A guide to closing down a project Feb 2011 Oracle VDI 3.2.2 Jan 2011 free VDI charts Jan 2011 Sun Founders Panel 2006 Dec 2010 Sutherland on Leadership Dec 2010 SocialChat: Efficiency of E20 Dec 2010 ALWAYS ON Desktop Virtualization Nov 2010 12,000 Desktops at JavaOne Nov 2010 SocialChat on Sharing Best Practices Oct 2010 Globe of Visitors Oct 2010 SocialChat about the Next Big Thing Oct 2010 Oracle VDI UX Story - Wireframes Oct 2010 What's a PC anyway? Oct 2010 SocialChat on Getting Things Done Oct 2010 SocialChat on Infoglut Oct 2010 IT Twenty Twenty Oct 2010 Desktop Virtualization Webcasts from OOW Oct 2010 Oracle VDI 3.2 Overview Sep 2010 Blog Usability Top 7 Sep 2010 100 and counting Aug 2010 Oracle'izing the VDI Blogs Aug 2010 SocialChat on Apple Aug 2010 SocialChat on Video Conferencing Aug 2010 Oracle VDI 3.2 - Features and Screenshots Aug 2010 SocialChat: Don't stop making waves Aug 2010 SocialChat: Giving Back to the Community Aug 2010 SocialChat on Learning in Meetings Aug 2010 iPAD's Natural User Interface Jul 2010 Last day for Sun Microsystems GmbH Jun 2010 SirValUse Celebration Snippets Jun 2010 10 years SirValUse - Happy Birthday! Jun 2010 Wim on Virtualization May 2010 New Home for Oracle VDI Apr 2010 Renaissance Slide Sorter Comments Apr 2010 Unboxing Sun Ray 3 Plus Apr 2010 Desktop Virtualisierung mit Sun VDI 3.1 Apr 2010 Blog Relaunch Mar 2010 Social Messaging Slides from CeBIT Mar 2010 Social Messaging Talk at CeBIT Feb 2010 Welcome Oracle Jan 2010 My last presentation at Sun Jan 2010 Ivan Sutherland on Leadership Jan 2010 Learning French with Sun VDI Jan 2010 Learning Danish with Sun Ray Jan 2010 VDI workshop in Nieuwegein Jan 2010 Happy New Year 2010 Jan 2010 On Creating Slides Dec 2009 Best VDI Ever Nov 2009 How to store the Big Bang Nov 2009 Social Enterprise Tools. Beipiel Sun. Nov 2009 Nov-19 Nov 2009 PDF and ODF links on your blog Nov 2009 Q&A on VDI and MySQL Cluster Nov 2009 Zürich next week: Swiss Intranet Summit 09 Nov 2009 Designing for a Sustainable World - World Usabiltiy Day, Nov-12 Nov 2009 How to export a desktop from VDI 3 Nov 2009 Virtualisation Roadshow in the UK Nov 2009 Project Wonderland at EDUCAUSE 09 Nov 2009 VDI Roadshow in Dublin, Nov-26, 2009 Nov 2009 Sun VDI at EDUCAUSE 09 Nov 2009 Sun VDI 3.1 Architecture and New Features Oct 2009 VDI 3.1 is Early-Access Sep 2009 Virtualization for MySQL on VMware Sep 2009 Silpion & 13. Stock Sommerparty Sep 2009 Sun Ray and VMware View 3.1.1 2009-08-31 New Set of Sun Ray Status Icons 2009-08-25 Virtualizing the VDI Core? 2009-08-23 World Usability Day Hamburg 2009 - CfP 2009-07-16 Rising Sun 2009-07-15 featuring twittermeme 2009-06-19 ISC09 Student Party on June-20 /Hamburg 2009-06-18 Before and behind the curtain of JavaOne 2009-06-09 20k desktops at JavaOne 2009-06-01 sweet microblogging 2009-05-25 VDI 3 - Why you need 3 VDI hosts and what you can do about that? 2009-05-21 IA Konferenz 2009 2009-05-20 Sun VDI 3 UX Story - Power of the Web 2009-05-06 Planet of Sun and Oracle User Experience Design 2009-04-22 Sun VDI 3 UX Story - User Research 2009-04-08 Sun VDI 3 UX Story - Concept Workshops 2009-04-06 Localized documentation for Sun Ray Connector for VMware View Manager 1.1 2009-04-03 Sun VDI 3 Press Release 2009-03-25 Sun VDI 3 launches today! 2009-03-25 Sun Ray Connector for VMware View Manager 1.1 Update 2009-03-11 desktop virtualization wiki relaunch 2009-03-06 VDI 3 at CeBIT hall 6, booth E36 2009-03-02 Keyboard layout problems with Sun Ray Connector for VMware VDM 2009-02-23 wikis.sun.com tips & tricks 2009-02-23 Sun VDI 3 is in Early Access 2009-02-09 VirtualCenter unable to decrypt passwords 2009-02-02 Sun & VMware Desktop Training 2009-01-30 VDI at next09? 2009-01-16 Sun VDI: How to use virtual machines with multiple network adapters 2009-01-07 Sun Ray and VMware View 2009-01-07 Hamburg World Usability Day 2008 - Webcasts 2009-01-06 Sun Ray Connector for VMware VDM slides 2008-12-15 mother of all demos 2008-12-08 Build your own Thumper 2008-12-03 Troubleshooting Sun Ray Connector for VMware VDM 2008-12-02 My Roller Tag Cloud 2008-11-28 Sun Ray Connector: SSL connection to VDM 2008-11-25 Setting up SSL and Sun Ray Connector for VMware VDM 2008-11-13 Inspiration for Today and Tomorrow 2008-10-23 Sun Ray Connector for VMware VDM released 2008-10-14 From Sketchpad to ILoveSketch 2008-10-09 Desktop Virtualization on Xing 2008-10-06 User Experience Forum on Xing 2008-10-06 Sun Ray Connector for VMware VDM certified 2008-09-17 Virtual Clouds over Las Vegas 2008-09-14 Bill Verplank sketches metaphors 2008-09-04 End of Early Access - Sun Ray Connector for VMware 2008-08-27 Early Access: Sun Ray Connector for VMware Virtual Desktop Manager 2008-08-12 Sun Virtual Desktop Connector - Insides on Recycling Part 2 2008-07-20 Sun Virtual Desktop Connector - Insides on Recycling Part 3 2008-07-20 Sun Virtual Desktop Connector - Insides on Recycling 2008-07-20 lost in wiki space 2008-07-07 Evolution of the Desktop 2008-06-17 Virtual Desktop Webcast 2008-06-16 Woodstock 2008-06-16 What's a Desktop PC anyway? 2008-06-09 Virtual-T-Box 2008-06-05 Virtualization Glossary 2008-05-06 Five User Experience Principles 2008-04-25 Virtualization News Feed 2008-04-21 Acetylcholinesterase - Second Season 2008-04-18 Acetylcholinesterase - End of Signal 2007-12-31 Produkt-Management ist... 2007-10-22 Usability Verbände, Verteiler und Netzwerke. 2007-10-02 The Meaning is the Message 2007-09-28 Visualization Methods 2007-09-10 Inhouse und Open Source Projekte – Usability verankern und Synergien nutzen 2007-09-03 Der Schwabe Darth Vader entdeckt das Virale Marketing 2007-08-29 Dick Hardt 3.0 on Identity 2.0 2007-08-27 quality of written text depends on the tool 2007-07-27 podcasts for reboot9 2007-06-04 It is the user's itch that need to be scratched 2007-05-25 A duel at reboot9 2007-05-14 Taxonomien und Folksonomien - Tagging als neues HCI-Element 2007-05-10 Dueling Interaction Models of Personal-Computing and Web-Computing 2007-03-01 22.März: Weizenbaum. Rebel at Work. /Filmpremiere Hamburg 2007-02-25 Bruce Sterling at UbiComp 2006 /webcast 2006-11-12 FSOSS 2006 /webcasts 2006-11-10 Highway 101 2006-11-09 User Experience Roundtable Hamburg: EuroGEL 2006 2006-11-08 Douglas Adams' Hyperland (BBC 1990) 2006-10-08 Taxonomien und Folksonomien – Tagging als neues HCI-Element 2006-09-13 Usability im Unternehmen 2006-09-13 Doug does HyperScope 2006-08-26 TED Talks and TechTalks 2006-08-21 Kai Krause über seine Freundschaft zu Douglas Adams 2006-07-20 Rebel At Work: Film Portrait on Weizenbaum 2006-07-04 Gabriele Fischer, mp3 2006-06-07 Dick Hardt at ETech 06 2006-06-05 Weinberger: From Control to Conversation 2006-04-16 Eye Tracking at User Experience Roundtable Hamburg 2006-04-14 dropping knowledge 2006-04-09 GEL 2005 2006-03-13 slide photos of reboot7 2006-03-04 Dick Hardt on Identity 2.0 2006-02-28 User Experience Newsletter #13: Versioning 2006-02-03 Ester Dyson on Choice and Happyness 2006-02-02 Requirements-Engineering im Spannungsfeld von Individual- und Produktsoftware 2006-01-15 User Experience Newsletter #12: Intuition Quiz 2005-11-30 User Experience und Requirements-Engineering für Software-Projekte 2005-10-31 Ivan Sutherland on "Research and Fun" 2005-10-18 Ars Electronica / Mensch und Computer 2005 2005-09-14 60 Jahre nach Memex: Über die Unvereinbarkeit von Desktop- und Web-Paradigma 2005-08-31 reboot 7 2005-06-30

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  • Can Microsoft Build Appliances?

    - by andrewbrust
    Billy Hollis, my Visual Studio Live! colleague and fellow Microsoft Regional Director said recently, and I am paraphrasing, that the computing world, especially on the consumer side, has shifted from one of building hardware and software that makes things possible to do, to building products and technologies that make things easy to do.  Billy crystalized things perfectly, as he often does. In this new world of “easy to do,” Apple has done very well and Microsoft has struggled.  In the old world, customers wanted a Swiss Army Knife, with the most gimmicks and gadgets possible.  In the new world, people want elegantly cutlery.  They may want cake cutters and utility knives too, but they don’t want one device that works for all three tasks.  People don’t want tools, they want utensils.  People don’t want machines.  They want appliances. Microsoft Appliances: They Do Exist Microsoft has built a few appliance-like devices.  I would say XBox 360 is an appliance,  It’s versatile, mind you, but it’s the kind of thing you plug in, turn on and use, as opposed to set-up, tune, and open up to upgrade the internals.  Windows Phone 7 is an appliance too.  It’s a true smartphone, unlike Windows Mobile which was a handheld computer with a radio stack.  Zune is an appliance too, and a nice one.  It hasn’t attained much traction in the market, but that’s probably because the seminal consumer computing appliance -- the iPod – got there so much more quickly. In the embedded world, Mediaroom, Microsoft’s set-top product for the cable industry (used by AT&T U-Verse and others) is an appliance.  So is Microsoft’s Sync technology, used in Ford automobiles.  Even on the enterprise side, Microsoft has an appliance: SQL Server Parallel Data Warehouse Edition (PDW) combines Microsoft software with select OEMs’ server, networking and storage hardware.  You buy the appliance units from the OEMs, plug them in, connect them and go. I would even say that Bing is an appliance.  Not in the hardware sense, mind you.  But from the software perspective, it’s a single-purpose product that you visit or run, use and then move on.  You don’t have to install it (except the iOS and Android native apps where it’s pretty straightforward), you don’t have to customize it, you don’t have to program it.  Basically, you just use it. Microsoft Appliances that Should Exist But Microsoft builds a bunch of things that are not appliances.  Media Center is not an appliance, and it most certainly should be.  Instead, it’s an app that runs on Windows 7.  It runs full-screen and you can use this configuration to conceal the fact that Windows is under it, but eventually something will cause you to abandon that masquerade (like Patch Tuesday). The next version of Windows Home Server won’t, in my opinion, be an appliance either.  Now that the Drive Extender technology is gone, and users can’t just add and remove drives into and from a single storage pool, the product is much more like a IT server and less like an appliance-premised one.  Much has been written about this decision by Microsoft.  I’ll just sum it up in one word: pity. Microsoft doesn’t have anything remotely appliance-like in the tablet category, either.  Until it does, it likely won’t have much market share in that space either.  And of course, the bulk of Microsoft’s product catalog on the business side is geared to enterprise machines and not personal appliances. Appliance DNA: They Gotta Have It. The consumerization of IT is real, because businesspeople are consumers too.  They appreciate the fit and finish of appliances at home, and they increasingly feel entitled to have it at work too.  Secure and reliable push email in a smartphone is necessary, but it isn’t enough.  People want great apps and a pleasurable user experience too.  The full Microsoft Office product is needed at work, but a PC with a keyboard and mouse, or maybe a touch screen that uses a stylus (or requires really small fingers), to run Office isn’t enough either.  People want a flawless touch experience available for the times they want to read and take quick notes.  Until Microsoft realizes this fully and internalizes it, it will suffer defeats in the consumer market and even setbacks in the business market.  Think about how slow the Office upgrade cycle is…now imagine if the next version of Office had a first-class alternate touch UI and consider the possible acceleration in adoption rates. Can Microsoft make the appliance switch?  Can the appliance mentality become pervasive at the company?  Can Microsoft hasten its release cycles dramatically and shed the “some assembly required” paradigm upon which many of its products are based?  Let’s face it, the chances that Microsoft won’t make this transition are significant. But there are also encouraging signs, and they should not be ignored.  The appliances we have already discussed, especially Xbox, Zune and Windows Phone 7, are the most obvious in this regard.  The fact that SQL Server has an appliance SKU now is a more subtle but perhaps also more significant outcome, because that product sits so smack in the middle of Microsoft’s enterprise stack.  Bing is encouraging too, especially given its integrated travel, maps and augmented reality capabilities.  As Bing gains market share, Microsoft has tangible proof that it can transform and win, even when everyone outside the company, and many within it, would bet otherwise. That Great Big Appliance in the Sky Perhaps the most promising (and evolving) proof points toward the appliance mentality, though, are Microsoft’s cloud offerings -- Azure and BPOS/Office 365.  While the cloud does not represent a physical appliance (quite the opposite in fact) its ability to make acquisition, deployment and use of technology simple for the user is absolutely an embodiment of the appliance mentality and spirit.  Azure is primarily a platform as a service offering; it doesn’t just provide infrastructure.  SQL Azure does likewise for databases.  And Office 365 does likewise for SharePoint, Exchange and Lync. You don’t administer, tune and manage servers; instead, you create databases or site collections or mailboxes and start using them. Upgrades come automatically, and it seems like releases will come more frequently.  Fault tolerance and content distribution is just there.  No muss.  No fuss.  You use these services; you don’t have to set them up and think about them.  That’s how appliances work.  To me, these signs point out that Microsoft has the full capability of transforming itself.  But there’s a lot of work ahead.  Microsoft may say they’re “all in” on the cloud, but the majority of the company is still oriented around its old products and models.  There needs to be a wholesale cultural transformation in Redmond.  It can happen, but product management, program management, the field and executive ranks must unify in the effort. So must partners, and even customers.  New leaders must rise up and Microsoft must be able to see itself as a winner.  If Microsoft does this, it could lock-in decades of new success, and be a standard business school case study for doing so.  If not, the company will have missed an opportunity, and may see its undoing.

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  • Building an OpenStack Cloud for Solaris Engineering, Part 1

    - by Dave Miner
    One of the signature features of the recently-released Solaris 11.2 is the OpenStack cloud computing platform.  Over on the Solaris OpenStack blog the development team is publishing lots of details about our version of OpenStack Havana as well as some tips on specific features, and I highly recommend reading those to get a feel for how we've leveraged Solaris's features to build a top-notch cloud platform.  In this and some subsequent posts I'm going to look at it from a different perspective, which is that of the enterprise administrator deploying an OpenStack cloud.  But this won't be just a theoretical perspective: I've spent the past several months putting together a deployment of OpenStack for use by the Solaris engineering organization, and now that it's in production we'll share how we built it and what we've learned so far.In the Solaris engineering organization we've long had dedicated lab systems dispersed among our various sites and a home-grown reservation tool for developers to reserve those systems; various teams also have private systems for specific testing purposes.  But as a developer, it can still be difficult to find systems you need, especially since most Solaris changes require testing on both SPARC and x86 systems before they can be integrated.  We've added virtual resources over the years as well in the form of LDOMs and zones (both traditional non-global zones and the new kernel zones).  Fundamentally, though, these were all still deployed in the same model: our overworked lab administrators set up pre-configured resources and we then reserve them.  Sounds like pretty much every traditional IT shop, right?  Which means that there's a lot of opportunity for efficiencies from greater use of virtualization and the self-service style of cloud computing.  As we were well into development of OpenStack on Solaris, I was recruited to figure out how we could deploy it to both provide more (and more efficient) development and test resources for the organization as well as a test environment for Solaris OpenStack.At this point, let's acknowledge one fact: deploying OpenStack is hard.  It's a very complex piece of software that makes use of sophisticated networking features and runs as a ton of service daemons with myriad configuration files.  The web UI, Horizon, doesn't often do a good job of providing detailed errors.  Even the command-line clients are not as transparent as you'd like, though at least you can turn on verbose and debug messaging and often get some clues as to what to look for, though it helps if you're good at reading JSON structure dumps.  I'd already learned all of this in doing a single-system Grizzly-on-Linux deployment for the development team to reference when they were getting started so I at least came to this job with some appreciation for what I was taking on.  The good news is that both we and the community have done a lot to make deployment much easier in the last year; probably the easiest approach is to download the OpenStack Unified Archive from OTN to get your hands on a single-system demonstration environment.  I highly recommend getting started with something like it to get some understanding of OpenStack before you embark on a more complex deployment.  For some situations, it may in fact be all you ever need.  If so, you don't need to read the rest of this series of posts!In the Solaris engineering case, we need a lot more horsepower than a single-system cloud can provide.  We need to support both SPARC and x86 VM's, and we have hundreds of developers so we want to be able to scale to support thousands of VM's, though we're going to build to that scale over time, not immediately.  We also want to be able to test both Solaris 11 updates and a release such as Solaris 12 that's under development so that we can work out any upgrade issues before release.  One thing we don't have is a requirement for extremely high availability, at least at this point.  We surely don't want a lot of down time, but we can tolerate scheduled outages and brief (as in an hour or so) unscheduled ones.  Thus I didn't need to spend effort on trying to get high availability everywhere.The diagram below shows our initial deployment design.  We're using six systems, most of which are x86 because we had more of those immediately available.  All of those systems reside on a management VLAN and are connected with a two-way link aggregation of 1 Gb links (we don't yet have 10 Gb switching infrastructure in place, but we'll get there).  A separate VLAN provides "public" (as in connected to the rest of Oracle's internal network) addresses, while we use VxLANs for the tenant networks. One system is more or less the control node, providing the MySQL database, RabbitMQ, Keystone, and the Nova API and scheduler as well as the Horizon console.  We're curious how this will perform and I anticipate eventually splitting at least the database off to another node to help simplify upgrades, but at our present scale this works.I had a couple of systems with lots of disk space, one of which was already configured as the Automated Installation server for the lab, so it's just providing the Glance image repository for OpenStack.  The other node with lots of disks provides Cinder block storage service; we also have a ZFS Storage Appliance that will help back-end Cinder in the near future, I just haven't had time to get it configured in yet.There's a separate system for Neutron, which is our Elastic Virtual Switch controller and handles the routing and NAT for the guests.  We don't have any need for firewalling in this deployment so we're not doing so.  We presently have only two tenants defined, one for the Solaris organization that's funding this cloud, and a separate tenant for other Oracle organizations that would like to try out OpenStack on Solaris.  Each tenant has one VxLAN defined initially, but we can of course add more.  Right now we have just a single /24 network for the floating IP's, once we get demand up to where we need more then we'll add them.Finally, we have started with just two compute nodes; one is an x86 system, the other is an LDOM on a SPARC T5-2.  We'll be adding more when demand reaches the level where we need them, but as we're still ramping up the user base it's less work to manage fewer nodes until then.My next post will delve into the details of building this OpenStack cloud's infrastructure, including how we're using various Solaris features such as Automated Installation, IPS packaging, SMF, and Puppet to deploy and manage the nodes.  After that we'll get into the specifics of configuring and running OpenStack itself.

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  • Clouds Everywhere But not a Drop of Rain – Part 3

    - by sxkumar
    I was sharing with you how a broad-based transformation such as cloud will increase agility and efficiency of an organization if process re-engineering is part of the plan.  I have also stressed on the key enterprise requirements such as “broad and deep solutions, “running your mission critical applications” and “automated and integrated set of capabilities”. Let me walk you through some key cloud attributes such as “elasticity” and “self-service” and what they mean for an enterprise class cloud. I will also talk about how we at Oracle have taken a very enterprise centric view to developing cloud solutions and how our products have been specifically engineered to address enterprise cloud needs. Cloud Elasticity and Enterprise Applications Requirements Easy and quick scalability for a short-period of time is the signature of cloud based solutions. It is this elasticity that allows you to dynamically redistribute your resources according to business priorities, helps increase your overall resource utilization, and reduces operational costs by allowing you to get the most out of your existing investment. Most public clouds are offering a instant provisioning mechanism of compute power (CPU, RAM, Disk), customer pay for the instance-hours(and bandwidth) they use, adding computing resources at peak times and removing them when they are no longer needed. This type of “just-in-time” serving of compute resources is well known for mid-tiers “state less” servers such as web application servers and web servers that just need another machine to start and run on it but what does it really mean for an enterprise application and its underlying data? Most enterprise applications are not as quite as “state less” and justifiably so. As such, how do you take advantage of cloud elasticity and make it relevant for your enterprise apps? This is where Cloud meets Grid Computing. At Oracle, we have invested enormous amount of time, energy and resources in creating enterprise grid solutions. All our technology products offer built-in elasticity via clustering and dynamic scaling. With products like Real Application Clusters (RAC), Automatic Storage Management, WebLogic Clustering, and Coherence In-Memory Grid, we allow all your enterprise applications to benefit from Cloud elasticity –both vertically and horizontally - without requiring any application changes. A number of technology vendors take a rather simplistic route of starting up additional or removing unneeded VM as the "Cloud Scale-Out" solution. While this may work for stateless mid-tier servers where load balancers can handle the addition and remove of instances transparently but following a similar approach for the database tier - often called as "database sharding" - requires significant application modification and typically does not work with off the shelf packaged applications. Technologies like Oracle Database Real Application Clusters, Automatic Storage Management, etc. on the other hand bring the benefits of incremental scalability and on-demand elasticity to ANY application by providing a simplified abstraction layers where the application does not need deal with data spread over multiple database instances. Rather they just talk to a single database and the database software takes care of aggregating resources across multiple hardware components. It is the technologies like these that truly make a cloud solution relevant for enterprises.  For customers who are looking for a next generation hardware consolidation platform, our engineered systems (e.g. Exadata, Exalogic) not only provide incredible amount of performance and capacity, they also reduce the data center complexity and simplify operations. Assemble, Deploy and Manage Enterprise Applications for Cloud Products like Oracle Virtual assembly builder (OVAB) resolve the complex problem of bringing the cloud speed to complex multi-tier applications. With assemblies, you can not only provision all components of a multi-tier application and wire them together by push of a button, other aspects of application lifecycle, such as real-time application testing, scale-up/scale-down, performance and availability monitoring, etc., are also automated using Oracle Enterprise Manager.  An essential criteria for an enterprise cloud to succeed is the ability to ensure business service levels especially when business users have either full visibility on the usage cost with a “show back” or a “charge back”. With Oracle Enterprise Manager 12c, we have created the most comprehensive cloud management solution in the industry that is capable of managing business service levels “applications-to-disk” in a enterprise private cloud – all from a single console. It is the only cloud management platform in the industry that allows you to deliver infrastructure, platform and application cloud services out of the box. Moreover, it offers integrated and complete lifecycle management of the cloud - including planning and set up, service delivery, operations management, metering and chargeback, etc .  Sounds unbelievable? Well, just watch this space for more details on how Oracle Enterprise Manager 12c is the nerve center of Oracle Cloud! Our cloud solution portfolio is also the broadest and most deep in the industry  - covering public, private, hybrid, Infrastructure, platform and applications clouds. It is no coincidence therefore that the Oracle Cloud today offers the most comprehensive set of public cloud services in the industry.  And to a large part, this has been made possible thanks to our years on investment in creating cloud enabling technologies.  Summary  But the intent of this blog post isn't to dwell on how great our solutions are (these are just some examples to illustrate how we at Oracle have approached this problem space). Rather it is to help you ask the right questions before you embark on your cloud journey.  So to summarize, here are the key takeaways.       It is critical that you are clear on why you are building the cloud. Successful organizations keep business benefits as the first and foremost cloud objective. On the other hand, those who approach this purely as a technology project are more likely to fail. Think about where you want to be in 3-5 years before you get started. Your long terms objectives should determine what your first step ought to be. As obvious as it may seem, more people than not make the first move without knowing where they are headed.  Don’t make the mistake of equating cloud to virtualization and Infrastructure-as-a-Service (IaaS). Spinning a VM on-demand will give some short term relief to your IT staff but is unlikely to solve your larger business problems. As such, even if IaaS is your first step towards a more comprehensive cloud, plan the roadmap around those higher level services before you begin. And ask your vendors on how they are going to be your partners in this journey. Capabilities like self-service access and chargeback/showback are absolutely critical if you really expect your cloud to be transformational. Your business won't see the full benefits of the cloud until it empowers them with same kind of control and transparency that they are used to while using a public cloud service.  Evaluate the benefits of integration, as opposed to blindly following the best-of-breed strategy. Integration is a huge challenge and more so in a cloud environment. There are enormous costs associated with stitching a solution out of disparate components and even more in maintaining it. Hope you found these ideas helpful. Looking forward to hearing your thoughts and experiences.

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