Fastest Java Matrix Multiplication

Introduction Matrix multiplication occupies a central role in scientific computing with an extremely wide range of applications. Many numerical procedures in linear algebra (e.g. solving linear systems, matrix inversion, factorizations, determinants) can essentially be reduced to matrix multiplication [5, 3]. Hence, there is great interest in investigating fast matrix multiplication algorithms, to accelerate matrix multiplication (and other numerical procedures in turn). SuanShu was already the fastest in matrix multiplication and hence linear algebra per our benchmark. SuanShu v3.0.0 benchmark Starting version 3.3.0, SuanShu has implemented an advanced algorithm for even faster matrix multiplication. It makes some operations 100x times faster those of our competitors! The new benchmark can be found here: SuanShu v3.3.0 benchmark In this article, we briefly describe our implementation of a matrix multiplication algorithm that dramatically accelerates dense matrix-matrix multiplication compared to the classical IJK algorithm. Parallel IJK We first describe the method against which our new algorithm is compared against, IJK. Here is the algorithm performing multiplication for is ,  is , and  is : for (i = 1; i < = m; i ++){ for (j = 1; j <= p; j ++){ for (k = 1; k <= n; k ++){ C[i,k] += A[i,j] * B[j,k]; } } } 1234567 for (i = 1; i < = m; i ++){    for (j = 1; j <= p; j ++){        for (k = 1; k <= n; k ++){            C[i,k] += A[i,j] * B[j,k];        }    }} In Suanshu, this is implemented in parallel; the outermost loop is passed to a  ParallelExecutor . As there are often more rows than threads available, the time complexity of this parallelized IJK is still roughly the same as IJK: ,...

FREE .NET/C# Numerical/Math library

On this Christmas Day, we are happy to announce that SuanShu.net is FREE for all! SuanShu.net has all the features as its Java sibling as well as has undergone the same many thousands of test cases daily. There are a tutorial and examples that show you how to build a SuanShu application in Visual Studio. One major advantage of using SuanShu.net over the Java version is that it integrates seamlessly with Microsoft Excel. By incorporating SuanShu library in your spreadsheet, you literally have access to hundreds of numerical algorithms when manipulating and analyzing your data, significantly enhancing Excel’s productivity. We hope that you enjoy using SuanShu.net in your work. If you have any interesting story, comments or feedback, we’d love to hear from you. Starting downloading SuanShu.net...

SuanShu 2.0

We are proud to announce the release of SuanShu 2.0! This release is the accumulation of customer feedbacks and our experience learnt in the last three years coding numerical computation algorithms. SuanShu 2.0 is a redesign of the software architecture, a rewrite of many modules, additions of new modules and functionalities driven by user demands and applications, numerous bug fixes as well as performance tuning. We believe that SuanShu 2.0 is the best numerical and statistical library ever available in Java, if not all, platform. Here are highlights of the new features available since 2.0. –          ordinary and partial differential equation solvers –          Optimization: Quadratic Programming,  Sequential Quadratic Programming, (Mixed) Integer Linear Programming, Semi-Definite Programming –          ARIMA fit –          LASSO and LARS –          Gaussian quadrature/integration –          Interpolation methods –          Trigonometric functions and physical constants –          Extreme Value Theory Continuing our tradition, we will still provide trial license and academic license for eligible schools and research institutes. Moreover, we now provide another way to get a FREE SuanShu license – the contribution license. If you are able to contribute code to the SuanShu library, you can get a permanent license. For more information, see: http://numericalmethod.com/suanshu/ We hope that you will find the new release of SuanShu more helpful than ever in your work. If you have any comments to help us improve, please do let us know. Happy birthday to TianTians and Merry Christmas to all!...

Using SuanShu on Amazon EC2

Cloud computing is very popular nowadays. Delegating your CPU-intensive computation (or simulation) to the cloud seems to be a smart choice. Many of our users asked if SuanShu can be run on Amazon’s Elastic Compute Cloud (EC2), because SuanShu license requires a MAC address and they have no control on which machine being used when they launch an EC2 instance. Here comes a good news! Amazon Web Service (AWS) now supports Elastic Network Interface (ENI), by which you can bind your EC2 instance to a specified network interface. Therefore, you can license your SuanShu against the MAC address of the ENI, and launch an instance with the same ENI and MAC address. For details, please visit the blog here. User guide for ENI can also be found...
NUMERICAL METHOD INC Selected as a Red Herring Top 100 Asia Tech Startup

NUMERICAL METHOD INC Selected as a Red Herring Top 100 Asia Tech Startup

Hong Kong, China – Numerical Method Incorporation Limited has won the Top 100 Asia award. Numerical Method Inc. publishes SuanShu, a Java math library, and AlgoQuant, an algorithmic/quantitative trading strategy research platform. Red Herring announced its Top 100 Asia award in recognition of the leading private companies from Asia, celebrating these startups’ innovations and technologies across their respective industries. Red Herring’s Top 100 list has become a mark of distinction for identifying promising new companies and entrepreneurs. Red Herring editors were among the first to recognize that companies such as Facebook, Twitter, Google, Yahoo, Skype, Salesforce.com, YouTube, and eBay would change the way we live and work. “Choosing the companies with the strongest potential was by no means a small feat,” said Alex Vieux, publisher and CEO of Red Herring. “After rigorous contemplation and discussion, we narrowed our list down from hundreds of candidates from across Asia to the Top 100 Winners. We believe Numerical Method Inc. embodies the vision, drive and innovation that define a successful entrepreneurial venture. Numerical Method Inc. should be proud of its accomplishment, as the competition was very strong.” Red Herring’s editorial staff evaluated the companies on both quantitative and qualitative criteria, such as financial performance, technology innovation, management quality, strategy, and market penetration. This assessment of potential is complemented by a review of the track record and standing of startups relative to their sector peers, allowing Red Herring to see past the “buzz” and make the list a valuable instrument of discovery and advocacy for the most promising new business models in Asia....