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  • Converting a bounded knapsack problem to 0/1 knapsack problem

    - by Ants
    I ran across a problem where goal was to use dynamic programming (instead of other approaches). There is a distance to be spanned, and a set of cables of different lengths. What is the minimum number of cables needed to span the distance exactly? To me this looked like a knapsack problem, but since there could be multiples of a particular length, it was a bounded knapsack problem, rather than a 0/1 knapsack problem. (Treat the value of each item to be its weight.) Taking the naive approach (and not caring about the expansion of the search space), the method I used to convert the bounded knapsack problem into a 0/1 knapsack problem, was simply break up the multiples into singles and apply the well-known dynamic programming algorithm. Unfortunately, this leads to sub-optimal results. For example, given cables: 1 x 10ft, 1 x 7ft, 1 x 6ft, 5 x 3ft, 6 x 2ft, 7 x 1ft If the target span is 13ft, the DP algorithm picks 7+6 to span the distance. A greedy algorithm would have picked 10+3, but it's a tie for minimum number of cables. The problem arises, when trying to span 15ft. The DP algorithm ended up picking 6+3+3+3 to get 4 cables, while the greedy algorithm correctly picks 10+3+2 for only 3 cables. Anyway, doing some light scanning of converting bounded to 0/1, it seems like the well-known approach to convert multiple items to { p, 2p, 4p ... }. My question is how does this conversion work if p+2p+4p does not add up to the number of multiple items. For example: I have 5 3ft cables. I can't very well add { 3, 2x3, 4x3 } because 3+2x3+4x3 5x3. Should I add { 3, 4x3 } instead? [I'm currently trying to grok the "Oregon Trail Knapsack Problem" paper, but it currently looks like the approach used there is not dynamic programming.]

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  • Marching squares: Finding multiple contours within one source field?

    - by TravisG
    Principally, this is a follow-up-question to a problem from a few weeks ago, even though this is about the algorithm in general without application to my actual problem. The algorithm basically searches through all lines in the picture, starting from the top left of it, until it finds a pixel that is a border. In pseudo-C++: int start = 0; for(int i=0; i<amount_of_pixels; ++i) { if(pixels[i] == border) { start = i; break; } } When it finds one, it starts the marching squares algorithm and finds the contour to whatever object the pixel belongs to. Let's say I have something like this: Where everything except the color white is a border. And have found the contour points of the first blob: For the general algorithm it's over. It found a contour and has done its job. How can I move on to the other two blobs to find their contours as well?

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  • Design pattern: static function call with input/output containers?

    - by Pavlo Dyban
    I work for a company in software research department. We use algorithms from our real software and wrap them so that we can use them for prototyping. Every time an algorithm interface changes, we need to adapt our wrappers respectively. Recently all algorithms have been refactored in such a manner that instead of accepting many different inputs and returning outputs via referenced parameters, they now accept one input data container and one output data container (the latter is passed by reference). Algorithm interface is limited to a static function call like that: class MyAlgorithm{ static bool calculate(MyAlgorithmInput input, MyAlgorithmOutput &output); } This is actually a very powerful design, though I have never seen it in a C++ programming environment before. Changes in the number of parameters and their data types are now encapsulated and they don't change the algorithm callback. In the latest algorithm which I have developed I used the same scheme. Now I want to know if this is a popular design pattern and what it is called.

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  • Is the Leptonica implementation of 'Modified Median Cut' not using the median at all?

    - by TheCodeJunkie
    I'm playing around a bit with image processing and decided to read up on how color quantization worked and after a bit of reading I found the Modified Median Cut Quantization algorithm. I've been reading the code of the C implementation in Leptonica library and came across something I thought was a bit odd. Now I want to stress that I am far from an expert in this area, not am I a math-head, so I am predicting that this all comes down to me not understanding all of it and not that the implementation of the algorithm is wrong at all. The algorithm states that the vbox should be split along the lagest axis and that it should be split using the following logic The largest axis is divided by locating the bin with the median pixel (by population), selecting the longer side, and dividing in the center of that side. We could have simply put the bin with the median pixel in the shorter side, but in the early stages of subdivision, this tends to put low density clusters (that are not considered in the subdivision) in the same vbox as part of a high density cluster that will outvote it in median vbox color, even with future median-based subdivisions. The algorithm used here is particularly important in early subdivisions, and 3is useful for giving visible but low population color clusters their own vbox. This has little effect on the subdivision of high density clusters, which ultimately will have roughly equal population in their vboxes. For the sake of the argument, let's assume that we have a vbox that we are in the process of splitting and that the red axis is the largest. In the Leptonica algorithm, on line 01297, the code appears to do the following Iterate over all the possible green and blue variations of the red color For each iteration it adds to the total number of pixels (population) it's found along the red axis For each red color it sum up the population of the current red and the previous ones, thus storing an accumulated value, for each red note: when I say 'red' I mean each point along the axis that is covered by the iteration, the actual color may not be red but contains a certain amount of red So for the sake of illustration, assume we have 9 "bins" along the red axis and that they have the following populations 4 8 20 16 1 9 12 8 8 After the iteration of all red bins, the partialsum array will contain the following count for the bins mentioned above 4 12 32 48 49 58 70 78 86 And total would have a value of 86 Once that's done it's time to perform the actual median cut and for the red axis this is performed on line 01346 It iterates over bins and check they accumulated sum. And here's the part that throws me of from the description of the algorithm. It looks for the first bin that has a value that is greater than total/2 Wouldn't total/2 mean that it is looking for a bin that has a value that is greater than the average value and not the median ? The median for the above bins would be 49 The use of 43 or 49 could potentially have a huge impact on how the boxes are split, even though the algorithm then proceeds by moving to the center of the larger side of where the matched value was.. Another thing that puzzles me a bit is that the paper specified that the bin with the median value should be located, but does not mention how to proceed if there are an even number of bins.. the median would be the result of (a+b)/2 and it's not guaranteed that any of the bins contains that population count. So this is what makes me thing that there are some approximations going on that are negligible because of how the split actually takes part at the center of the larger side of the selected bin. Sorry if it got a bit long winded, but I wanted to be as thoroughas I could because it's been driving me nuts for a couple of days now ;)

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  • Generic Event Generator and Handler from User Supplied Types?

    - by JaredBroad
    I'm trying to allow the user to supply custom data and manage the data with custom types. The user's algorithm will get time synchronized events pushed into the event handlers they define. I'm not sure if this is possible but here's the "proof of concept" code I'd like to build. It doesn't detect T in the for loop: "The type or namespace name 'T' could not be found" class Program { static void Main(string[] args) { Algorithm algo = new Algorithm(); Dictionary<Type, string[]> userDataSources = new Dictionary<Type, string[]>(); // "User" adding custom type and data source for algorithm to consume userDataSources.Add(typeof(Weather), new string[] { "temperature data1", "temperature data2" }); for (int i = 0; i < 2; i++) { foreach (Type T in userDataSources.Keys) { string line = userDataSources[typeof(T)][i]; //Iterate over CSV data.. var userObj = new T(line); algo.OnData < typeof(T) > (userObj); } } } //User's algorithm pattern. interface IAlgorithm<TData> where TData : class { void OnData<TData>(TData data); } //User's algorithm. class Algorithm : IAlgorithm<Weather> { //Handle Custom User Data public void OnData<Weather>(Weather data) { Console.WriteLine(data.date.ToString()); Console.ReadKey(); } } //Example "user" custom type. public class Weather { public DateTime date = new DateTime(); public double temperature = 0; public Weather(string line) { Console.WriteLine("Initializing weather object with: " + line); date = DateTime.Now; temperature = -1; } } }

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  • Cooperative linux vs vm

    - by Rhythmic Algorithm
    What are the advantages / disadvantages of using cooperative linux like portable ubuntu for example compared to a qemu or any other virtual machine installation. Is one option notably faster than the other plus and other things that should be taken into consideration.

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  • How to stop RAID5 array while it is shown to be busy?

    - by RCola
    I have a raid5 array and need to stop it, but while trying to stop it getting error. # cat /proc/mdstat Personalities : [linear] [multipath] [raid0] [raid1] [raid6] [raid5] [raid4] [raid10] md0 : active raid5 sde1[3](F) sdc1[4](F) sdf1[2] sdd1[1] 2120320 blocks level 5, 32k chunk, algorithm 2 [3/2] [_UU] unused devices: <none> # mdadm --stop mdadm: metadata format 00.90 unknown, ignored. mdadm: metadata format 00.90 unknown, ignored. mdadm: No devices given. # mdadm --stop /dev/md0 mdadm: metadata format 00.90 unknown, ignored. mdadm: metadata format 00.90 unknown, ignored. mdadm: fail to stop array /dev/md0: Device or resource busy and # lsof | grep md0 md0_raid5 965 root cwd DIR 8,1 4096 2 / md0_raid5 965 root rtd DIR 8,1 4096 2 / md0_raid5 965 root txt unknown /proc/965/exe # cat /proc/mdstat Personalities : [linear] [multipath] [raid0] [raid1] [raid6] [raid5] [raid4] [raid10] md0 : active raid5 sde1[3](F) sdc1[4](F) sdf1[2] sdd1[1] 2120320 blocks level 5, 32k chunk, algorithm 2 [3/2] [_UU] # grep md0 /proc/mdstat md0 : active raid5 sde1[3](F) sdc1[4](F) sdf1[2] sdd1[1] # grep md0 /proc/partitions 9 0 2120320 md0 While booting, md1 is mounted ok but md0 failed for some unknown reason # dmesg | grep md[0-9] [ 4.399658] raid5: allocated 3179kB for md1 [ 4.400432] raid5: raid level 5 set md1 active with 3 out of 3 devices, algorithm 2 [ 4.400678] md1: detected capacity change from 0 to 2121793536 [ 4.403135] md1: unknown partition table [ 38.937932] Filesystem "md1": Disabling barriers, trial barrier write failed [ 38.941969] XFS mounting filesystem md1 [ 41.058808] Ending clean XFS mount for filesystem: md1 [ 46.325684] raid5: allocated 3179kB for md0 [ 46.327103] raid5: raid level 5 set md0 active with 2 out of 3 devices, algorithm 2 [ 46.330620] md0: detected capacity change from 0 to 2171207680 [ 46.335598] md0: unknown partition table [ 46.410195] md: recovery of RAID array md0 [ 117.970104] md: md0: recovery done. # cat /proc/mdstat Personalities : [linear] [multipath] [raid0] [raid1] [raid6] [raid5] [raid4] [raid10] md0 : active raid5 sde1[0] sdf1[2] sdd1[1] 2120320 blocks level 5, 32k chunk, algorithm 2 [3/3] [UUU] md1 : active raid5 sdc2[0] sdf2[2] sde2[3](S) sdd2[1] 2072064 blocks level 5, 128k chunk, algorithm 2 [3/3] [UUU]

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  • A brief note for customers running SOA Suite on AIX platforms

    - by christian
    When running Oracle SOA Suite with IBM JVMs on the AIX platform, we have seen performance slowdowns and/or memory leaks. On occasion, we have even encountered some OutOfMemoryError conditions and the concomittant Java coredump. If you are experiencing this issue, the resolution may be to configure -Dsun.reflect.inflationThreshold=0 in your JVM startup parameters. https://www.ibm.com/developerworks/java/library/j-nativememory-aix/ contains a detailed discussion of the IBM AIX JVM memory model, but I will summarize my interpretation and understanding of it in the context of SOA Suite, below. Java ClassLoaders on IBM JVMs are allocated a native memory area into which they are anticipated to map such things as jars loaded from the filesystem. This is an excellent memory optimization, as the file can be loaded into memory once and then shared amongst many JVMs on the same host, allowing for excellent horizontal scalability on AIX hosts. However, Java ClassLoaders are not used exclusively for loading files from disk. A performance optimization by the Oracle Java language developers enables reflectively accessed data to optimize from a JNI call into Java bytecodes which are then amenable to hotspot optimizations, amongst other things. This performance optimization is called inflation, and it is executed by generating a sun.reflect.DelegatingClassLoader instance dynamically to inject the Java bytecode into the virtual machine. It is generally considered an excellent optimization. However, it interacts very negatively with the native memory area allocated by the IBM JVM, effectively locking out memory that could otherwise be used by the Java process. SOA Suite and WebLogic are both very large users of reflection code. They reflectively use many code paths in their operation, generating lots of DelegatingClassLoaders in normal operation. The IBM JVM slowdown and subsequent OutOfMemoryError are as a direct result of the Java memory consumed by the DelegatingClassLoader instances generated by SOA Suite and WebLogic. Java garbage collection runs more frequently to try and keep memory available, until it can no longer do so and throws OutOfMemoryError. The setting sun.reflect.inflationThreshold=0 disables this optimization entirely, never allowing the JVM to generate the optimized reflection code. IBM JVMs are susceptible to this issue primarily because all Java ClassLoaders have this native memory allocation, which is shared with the regular Java heap. Oracle JVMs don't automatically give all ClassLoaders a native memory area, and my understanding is that jar files are never mapped completely from shared memory in the same way as IBM does it. This results in different behaviour characteristics on IBM vs Oracle JVMs.

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  • How to get compatibility between C# and SQL2k8 AES Encryption?

    - by Victor Rodrigues
    I have an AES encryption being made on two columns: one of these columns is stored at a SQL Server 2000 database; the other is stored at a SQL Server 2008 database. As the first column's database (2000) doesn't have native functionality for encryption / decryption, we've decided to do the cryptography logic at application level, with .NET classes, for both. But as the second column's database (2008) allow this kind of functionality, we'd like to make the data migration using the database functions to be faster, since the data migration in SQL 2k is much smaller than this second and it will last more than 50 hours because of being made at application level. My problem started at this point: using the same key, I didn't achieve the same result when encrypting a value, neither the same result size. Below we have the full logic in both sides.. Of course I'm not showing the key, but everything else is the same: private byte[] RijndaelEncrypt(byte[] clearData, byte[] Key) { var memoryStream = new MemoryStream(); Rijndael algorithm = Rijndael.Create(); algorithm.Key = Key; algorithm.IV = InitializationVector; var criptoStream = new CryptoStream(memoryStream, algorithm.CreateEncryptor(), CryptoStreamMode.Write); criptoStream.Write(clearData, 0, clearData.Length); criptoStream.Close(); byte[] encryptedData = memoryStream.ToArray(); return encryptedData; } private byte[] RijndaelDecrypt(byte[] cipherData, byte[] Key) { var memoryStream = new MemoryStream(); Rijndael algorithm = Rijndael.Create(); algorithm.Key = Key; algorithm.IV = InitializationVector; var criptoStream = new CryptoStream(memoryStream, algorithm.CreateDecryptor(), CryptoStreamMode.Write); criptoStream.Write(cipherData, 0, cipherData.Length); criptoStream.Close(); byte[] decryptedData = memoryStream.ToArray(); return decryptedData; } This is the SQL Code sample: open symmetric key columnKey decryption by password = N'{pwd!!i_ll_not_show_it_here}' declare @enc varchar(max) set @enc = dbo.VarBinarytoBase64(EncryptByKey(Key_GUID('columnKey'), 'blablabla')) select LEN(@enc), @enc This varbinaryToBase64 is a tested sql function we use to convert varbinary to the same format we use to store strings in the .net application. The result in C# is: eg0wgTeR3noWYgvdmpzTKijkdtTsdvnvKzh+uhyN3Lo= The same result in SQL2k8 is: AI0zI7D77EmqgTQrdgMBHAEAAACyACXb+P3HvctA0yBduAuwPS4Ah3AB4Dbdj2KBGC1Dk4b8GEbtXs5fINzvusp8FRBknF15Br2xI1CqP0Qb/M4w I just didn't get yet what I'm doing wrong. Do you have any ideas? EDIT: One point I think is crucial: I have one Initialization Vector at my C# code, 16 bytes. This IV is not set at SQL symmetric key, could I do this? But even not filling the IV in C#, I get very different results, both in content and length.

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  • Optimizing Solaris 11 SHA-1 on Intel Processors

    - by danx
    SHA-1 is a "hash" or "digest" operation that produces a 160 bit (20 byte) checksum value on arbitrary data, such as a file. It is intended to uniquely identify text and to verify it hasn't been modified. Max Locktyukhin and others at Intel have improved the performance of the SHA-1 digest algorithm using multiple techniques. This code has been incorporated into Solaris 11 and is available in the Solaris Crypto Framework via the libmd(3LIB), the industry-standard libpkcs11(3LIB) library, and Solaris kernel module sha1. The optimized code is used automatically on systems with a x86 CPU supporting SSSE3 (Intel Supplemental SSSE3). Intel microprocessor architectures that support SSSE3 include Nehalem, Westmere, Sandy Bridge microprocessor families. Further optimizations are available for microprocessors that support AVX (such as Sandy Bridge). Although SHA-1 is considered obsolete because of weaknesses found in the SHA-1 algorithm—NIST recommends using at least SHA-256, SHA-1 is still widely used and will be with us for awhile more. Collisions (the same SHA-1 result for two different inputs) can be found with moderate effort. SHA-1 is used heavily though in SSL/TLS, for example. And SHA-1 is stronger than the older MD5 digest algorithm, another digest option defined in SSL/TLS. Optimizations Review SHA-1 operates by reading an arbitrary amount of data. The data is read in 512 bit (64 byte) blocks (the last block is padded in a specific way to ensure it's a full 64 bytes). Each 64 byte block has 80 "rounds" of calculations (consisting of a mixture of "ROTATE-LEFT", "AND", and "XOR") applied to the block. Each round produces a 32-bit intermediate result, called W[i]. Here's what each round operates: The first 16 rounds, rounds 0 to 15, read the 512 bit block 32 bits at-a-time. These 32 bits is used as input to the round. The remaining rounds, rounds 16 to 79, use the results from the previous rounds as input. Specifically for round i it XORs the results of rounds i-3, i-8, i-14, and i-16 and rotates the result left 1 bit. The remaining calculations for the round is a series of AND, XOR, and ROTATE-LEFT operators on the 32-bit input and some constants. The 32-bit result is saved as W[i] for round i. The 32-bit result of the final round, W[79], is the SHA-1 checksum. Optimization: Vectorization The first 16 rounds can be vectorized (computed in parallel) because they don't depend on the output of a previous round. As for the remaining rounds, because of step 2 above, computing round i depends on the results of round i-3, W[i-3], one can vectorize 3 rounds at-a-time. Max Locktyukhin found through simple factoring, explained in detail in his article referenced below, that the dependencies of round i on the results of rounds i-3, i-8, i-14, and i-16 can be replaced instead with dependencies on the results of rounds i-6, i-16, i-28, and i-32. That is, instead of initializing intermediate result W[i] with: W[i] = (W[i-3] XOR W[i-8] XOR W[i-14] XOR W[i-16]) ROTATE-LEFT 1 Initialize W[i] as follows: W[i] = (W[i-6] XOR W[i-16] XOR W[i-28] XOR W[i-32]) ROTATE-LEFT 2 That means that 6 rounds could be vectorized at once, with no additional calculations, instead of just 3! This optimization is independent of Intel or any other microprocessor architecture, although the microprocessor has to support vectorization to use it, and exploits one of the weaknesses of SHA-1. Optimization: SSSE3 Intel SSSE3 makes use of 16 %xmm registers, each 128 bits wide. The 4 32-bit inputs to a round, W[i-6], W[i-16], W[i-28], W[i-32], all fit in one %xmm register. The following code snippet, from Max Locktyukhin's article, converted to ATT assembly syntax, computes 4 rounds in parallel with just a dozen or so SSSE3 instructions: movdqa W_minus_04, W_TMP pxor W_minus_28, W // W equals W[i-32:i-29] before XOR // W = W[i-32:i-29] ^ W[i-28:i-25] palignr $8, W_minus_08, W_TMP // W_TMP = W[i-6:i-3], combined from // W[i-4:i-1] and W[i-8:i-5] vectors pxor W_minus_16, W // W = (W[i-32:i-29] ^ W[i-28:i-25]) ^ W[i-16:i-13] pxor W_TMP, W // W = (W[i-32:i-29] ^ W[i-28:i-25] ^ W[i-16:i-13]) ^ W[i-6:i-3]) movdqa W, W_TMP // 4 dwords in W are rotated left by 2 psrld $30, W // rotate left by 2 W = (W >> 30) | (W << 2) pslld $2, W_TMP por W, W_TMP movdqa W_TMP, W // four new W values W[i:i+3] are now calculated paddd (K_XMM), W_TMP // adding 4 current round's values of K movdqa W_TMP, (WK(i)) // storing for downstream GPR instructions to read A window of the 32 previous results, W[i-1] to W[i-32] is saved in memory on the stack. This is best illustrated with a chart. Without vectorization, computing the rounds is like this (each "R" represents 1 round of SHA-1 computation): RRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRR With vectorization, 4 rounds can be computed in parallel: RRRRRRRRRRRRRRRRRRRR RRRRRRRRRRRRRRRRRRRR RRRRRRRRRRRRRRRRRRRR RRRRRRRRRRRRRRRRRRRR Optimization: AVX The new "Sandy Bridge" microprocessor architecture, which supports AVX, allows another interesting optimization. SSSE3 instructions have two operands, a input and an output. AVX allows three operands, two inputs and an output. In many cases two SSSE3 instructions can be combined into one AVX instruction. The difference is best illustrated with an example. Consider these two instructions from the snippet above: pxor W_minus_16, W // W = (W[i-32:i-29] ^ W[i-28:i-25]) ^ W[i-16:i-13] pxor W_TMP, W // W = (W[i-32:i-29] ^ W[i-28:i-25] ^ W[i-16:i-13]) ^ W[i-6:i-3]) With AVX they can be combined in one instruction: vpxor W_minus_16, W, W_TMP // W = (W[i-32:i-29] ^ W[i-28:i-25] ^ W[i-16:i-13]) ^ W[i-6:i-3]) This optimization is also in Solaris, although Sandy Bridge-based systems aren't widely available yet. As an exercise for the reader, AVX also has 256-bit media registers, %ymm0 - %ymm15 (a superset of 128-bit %xmm0 - %xmm15). Can %ymm registers be used to parallelize the code even more? Optimization: Solaris-specific In addition to using the Intel code described above, I performed other minor optimizations to the Solaris SHA-1 code: Increased the digest(1) and mac(1) command's buffer size from 4K to 64K, as previously done for decrypt(1) and encrypt(1). This size is well suited for ZFS file systems, but helps for other file systems as well. Optimized encode functions, which byte swap the input and output data, to copy/byte-swap 4 or 8 bytes at-a-time instead of 1 byte-at-a-time. Enhanced the Solaris mdb(1) and kmdb(1) debuggers to display all 16 %xmm and %ymm registers (mdb "$x" command). Previously they only displayed the first 8 that are available in 32-bit mode. Can't optimize if you can't debug :-). Changed the SHA-1 code to allow processing in "chunks" greater than 2 Gigabytes (64-bits) Performance I measured performance on a Sun Ultra 27 (which has a Nehalem-class Xeon 5500 Intel W3570 microprocessor @3.2GHz). Turbo mode is disabled for consistent performance measurement. Graphs are better than words and numbers, so here they are: The first graph shows the Solaris digest(1) command before and after the optimizations discussed here, contained in libmd(3LIB). I ran the digest command on a half GByte file in swapfs (/tmp) and execution time decreased from 1.35 seconds to 0.98 seconds. The second graph shows the the results of an internal microbenchmark that uses the Solaris libpkcs11(3LIB) library. The operations are on a 128 byte buffer with 10,000 iterations. The results show operations increased from 320,000 to 416,000 operations per second. Finally the third graph shows the results of an internal kernel microbenchmark that uses the Solaris /kernel/crypto/amd64/sha1 module. The operations are on a 64Kbyte buffer with 100 iterations. third graph shows the results of an internal kernel microbenchmark that uses the Solaris /kernel/crypto/amd64/sha1 module. The operations are on a 64Kbyte buffer with 100 iterations. The results show for 1 kernel thread, operations increased from 410 to 600 MBytes/second. For 8 kernel threads, operations increase from 1540 to 1940 MBytes/second. Availability This code is in Solaris 11 FCS. It is available in the 64-bit libmd(3LIB) library for 64-bit programs and is in the Solaris kernel. You must be running hardware that supports Intel's SSSE3 instructions (for example, Intel Nehalem, Westmere, or Sandy Bridge microprocessor architectures). The easiest way to determine if SSSE3 is available is with the isainfo(1) command. For example, nehalem $ isainfo -v $ isainfo -v 64-bit amd64 applications sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov amd_sysc cx8 tsc fpu 32-bit i386 applications sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov sep cx8 tsc fpu If the output also shows "avx", the Solaris executes the even-more optimized 3-operand AVX instructions for SHA-1 mentioned above: sandybridge $ isainfo -v 64-bit amd64 applications avx xsave pclmulqdq aes sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov amd_sysc cx8 tsc fpu 32-bit i386 applications avx xsave pclmulqdq aes sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov sep cx8 tsc fpu No special configuration or setup is needed to take advantage of this code. Solaris libraries and kernel automatically determine if it's running on SSSE3 or AVX-capable machines and execute the correctly-tuned code for that microprocessor. Summary The Solaris 11 Crypto Framework, via the sha1 kernel module and libmd(3LIB) and libpkcs11(3LIB) libraries, incorporated a useful SHA-1 optimization from Intel for SSSE3-capable microprocessors. As with other Solaris optimizations, they come automatically "under the hood" with the current Solaris release. References "Improving the Performance of the Secure Hash Algorithm (SHA-1)" by Max Locktyukhin (Intel, March 2010). The source for these SHA-1 optimizations used in Solaris "SHA-1", Wikipedia Good overview of SHA-1 FIPS 180-1 SHA-1 standard (FIPS, 1995) NIST Comments on Cryptanalytic Attacks on SHA-1 (2005, revised 2006)

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  • WPF Layout algorithm woes - control will resize, but not below some arbitrary value.

    - by Quantumplation
    I'm working on an application for a client, and one of the requirements is the ability to make appointments, and display the current week's appointments in a visual format, much like in Google Calender's or Microsoft Office. I found a great (3 part) article on codeproject, in which he builds a "RangePanel", and composes one for each "period" (for example, the work day.) You can find part 1 here: http://www.codeproject.com/KB/WPF/OutlookWpfCalendarPart1.aspx The code presents, but seems to choose an arbitrary height value overall (440.04), and won't resize below that without clipping. What I mean to say, is that the window/container will resize, but it just cuts off the bottom of the control, instead of recalculating the height of the range panels, and the controls in the range panels representing the appointment. It will resize and recalculate for greater values, but not less. Code-wise, what's happening is that when you resize below that value, first the "MeasureOverride" is called with the correct "new height". However, by the time the "ArrangeOverride" method is called, it's passing the same 440.04 value as the height to arrange to. I need to find a solution/workaround, but any information that you can provide that might direct me for things to look into would also be greatly appreciated ( I understand how frustrating it is to debug code when you don't have the codebase in front of you. :) ) The code for the various Arrange and Measure functions are provided below. The "CalendarView" control has a "CalendarViewContentPresenter", which handles several periods. Then, the periods have a "CalendarPeriodContentPresenter", which handles each "block" of appointments. Finally, the "RangePanel" has it's own implementation. (To be honest, i'm still a bit hazy on how the control works, so if my explanations are a bit hazy, the article I linked probably has a more cogent explanation. :) ) CalendarViewContentPresenter: protected override Size ArrangeOverride(Size finalSize) { int columnCount = this.CalendarView.Periods.Count; Size columnSize = new Size(finalSize.Width / columnCount, finalSize.Height); double elementX = 0; foreach (UIElement element in this.visualChildren) { element.Arrange(new Rect(new Point(elementX, 0), columnSize)); elementX = elementX + columnSize.Width; } return finalSize; } protected override Size MeasureOverride(Size constraint) { this.GenerateVisualChildren(); this.GenerateListViewItemVisuals(); // If it's coming back infinity, just return some value. if (constraint.Width == Double.PositiveInfinity) constraint.Width = 10; if (constraint.Height == Double.PositiveInfinity) constraint.Height = 10; return constraint; } CalendarViewPeriodPersenter: protected override Size ArrangeOverride(Size finalSize) { foreach (UIElement element in this.visualChildren) { element.Arrange(new Rect(new Point(0, 0), finalSize)); } return finalSize; } protected override Size MeasureOverride(Size constraint) { this.GenerateVisualChildren(); return constraint; } RangePanel: protected override Size ArrangeOverride(Size finalSize) { double containerRange = (this.Maximum - this.Minimum); foreach (UIElement element in this.Children) { double begin = (double)element.GetValue(RangePanel.BeginProperty); double end = (double)element.GetValue(RangePanel.EndProperty); double elementRange = end - begin; Size size = new Size(); size.Width = (Orientation == Orientation.Vertical) ? finalSize.Width : elementRange / containerRange * finalSize.Width; size.Height = (Orientation == Orientation.Vertical) ? elementRange / containerRange * finalSize.Height : finalSize.Height; Point location = new Point(); location.X = (Orientation == Orientation.Vertical) ? 0 : (begin - this.Minimum) / containerRange * finalSize.Width; location.Y = (Orientation == Orientation.Vertical) ? (begin - this.Minimum) / containerRange * finalSize.Height : 0; element.Arrange(new Rect(location, size)); } return finalSize; } protected override Size MeasureOverride(Size availableSize) { foreach (UIElement element in this.Children) { element.Measure(availableSize); } // Constrain infinities if (availableSize.Width == double.PositiveInfinity) availableSize.Width = 10; if (availableSize.Height == double.PositiveInfinity) availableSize.Height = 10; return availableSize; }

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  • How do you solve the 15-puzzle with A-Star or Dijkstra's Algorithm?

    - by Sean
    I've read in one of my AI books that popular algorithms (A-Star, Dijkstra) for path-finding in simulation or games is also used to solve the well-known "15-puzzle". Can anyone give me some pointers on how I would reduce the 15-puzzle to a graph of nodes and edges so that I could apply one of these algorithms? If I were to treat each node in the graph as a game state then wouldn't that tree become quite large? Or is that just the way to do it?

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  • Java Compiler: Optimization of "cascaded" ifs and best practices?

    - by jens
    Hello, does the Java Compiler optimize a statement like this if (a == true) { if (b == true) { if (c == true) { if(d == true) { //code to process stands here } } } } to if (a == true && b==true && c==true && d == true) So thats my first question: Do both take exactly the same "CPU Cycles" or is the first variant "slowlier". My Second questin is, is the first variant with the cascaded if considered bad programming style as it is so verbose? (I like the first variant as I can better logically group my expressions and better comment them (my if statements are more complex than in the example), but maybe thats bad proramming style?) and even slowlier, thats why I am asking... Thanks Jens

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  • Which DHT algorithm to use (if I want to join two separate DHTs)?

    - by webdreamer
    I've been looking into some DHT systems, specially Pastry and Chord. I've read some concerns about Chord's reaction to churn, though I believe that won't be a problem for the task I have at hands. I'm implementing some sort of social network service that doesn't rely on any central servers for a course project. I need the DHT for the lookups. Now I don't know of all the servers in the network in the beginning. As I've stated, there's no main tracker server. It works this way: each client has three dedicated servers. The three servers have the profile of the client, and it's wall, it's personal info, replicated. I only get to know about other group of servers when the user adds a friend (inputing the client's address). So I would create two separate DHTs on the two groups of three servers and when they friend each other I would like to join the DHTs. I would like to this consistently. I haven't had a lot of time to get all that familiar with the protocols, so I would like to know which one is better if I want to join the two separate DHTs?

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  • If I write an algorithm to encrypt a file, are their tools available to break the encryption?

    - by Andrew
    I have an idea for encryption that I could program fairly easily to encrypt some local text file. Given that my approach is novel, and does not use any of the industry standard encryption techniques, would I be able to test the strength of my encryption using 'cracker' apps or suchlike? Or do all those tools rely on advanced knowledge of the encryption process (or intercepted 'keys'), meaning I'd have to build my own cracker for testing?

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  • Defining < for STL sort algorithm - operator overload, functor or standalone function?

    - by Andy
    I have a stl::list containing Widget class objects. They need to be sorted according to two members in the Widget class. For the sorting to work, I need to define a less-than comparator comparing two Widget objects. There seems to be a myriad of ways to do it. From what I can gather, one can either: a. Define a comparison operator overload in the class: bool Widget::operator< (const Widget &rhs) const b. Define a standalone function taking two Widgets: bool operator<(const Widget& lhs, const Widget& rhs); And then make the Widget class a friend of it: class Widget { // Various class definitions ... friend bool operator<(const Widget& lhs, const Widget& rhs); }; c. Define a functor and then include it as a parameter when calling the sort function: class Widget_Less : public binary_function<Widget, Widget, bool> { bool operator()(const Widget &lhs, const Widget& rhs) const; }; Does anybody know which method is better? In particular I am interested to know if I should do 1 or 2. I searched the book Effective STL by Scott Meyer but unfortunately it does not have anything to say about this. Thank you for your reply.

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  • What is jasper report's algorithm for using a data source?

    - by spderosso
    Hi, I have created my custom data source by implementing the interface JRDataSource. This interface looks like this: public interface JRDataSource { /** * Tries to position the cursor on the next element in the data source. * @return true if there is a next record, false otherwise * @throws JRException if any error occurs while trying to move to the next element */ public boolean next() throws JRException; /** * Gets the field value for the current position. * @return an object containing the field value. The object type must be the field object type. */ public Object getFieldValue(JRField jrField) throws JRException; } My question is the following: In what way does jasper report call this functions for obtaining the fields in the .jrxml. E.g: if( next() )){ call getFieldValue for every field present in the page header while( next() ){ call getFieldValue for every field present in detail part } call getFieldValue for every field present the footer } The previous is just an example, experimentally in fact I found out that it is actually not like that. So my question arised. Thanks!

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  • What is the best algorithm to locate a point in an image file?

    - by suugaku
    Hi all, I want to create a mark sheet recognizer. Here is the description: My system uses black and white color scheme. The mark sheet paper has a small black rectangle on each corner and an additional small black rectangle, to determine orientation, near one of the previous rectangles. The paper is scanned to yield an image (in bmp format for example). The first step is to locate these five references in image as eficient as possible. My rough idea is to trace row by row and from left to right for each row. It sounds very slow I think. Is there any better way to do that? Thank you in advance. regards, Suugaku

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