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Written by Douglas Andrade
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Monday, 09 April 2012 21:43 |
AMD OpenCL WebinarStay tuned for upcoming AMD OpenCL webinars. These videos are quite instructive and they provide a manufacturer's standpoint to build parallel applications using OpenCL. If it gets technical beyond the point of memory model and shared memory, you can just skip past the overtechnicality :)
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Written by Douglas Andrade
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Friday, 30 March 2012 01:00 |
Stanford Open CoursesIf you haven't checked the Stanford (and other) Open Courses at https://www.coursera.org/ , make sure not to miss them. These are great high level courses in many fields. If you did and are wondering how to use OpenCL to implement codes in the fields of Cryptography, Natural Language Processing (NLP) or Probabilistic Models (PGMs), feel free to post in our forum or send an e-mail and we'll be glad to work some accelerated algorithms toghether.
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Written by Douglas Andrade
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Sunday, 18 March 2012 00:03 |
C# Naive BayesThe Naive Bayes classifier is a machine learning tool widely used to classify text. In particular, it is an efficient tool to classify SPAM mail from useful ones. We at CMSoft have written a C# Naive Bayes implementation which we intend to include in OpenCLTemplate. We don't use OpenCL in this implementation at the moment because the algorithm is rather serial and it works quite well as it is. Please feel free to download and email or post any difficulties you find. We intend to write a brief tutorial in the near future. Download CMSoft's Naive Bayes C# class.
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Written by Douglas Andrade
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Friday, 02 March 2012 15:04 |
OpenCL Maturity Increasing It seems that OpenCL maturity keeps growing, leading to more stable and consolidated performance regarding both host code and its C99 adaptation for kernels. This article underlines how OpenCL is increasingly gaining more space as its major weakness (being too "green") continues to fade.
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Written by Douglas Andrade
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Sunday, 12 February 2012 11:12 |
OpenCL TrendsOpenCL seems to be gaining momentum as manufacturers realize the enormous potential of unleashing massive parallelism with CPUs and GPUs with reusable code that can be compiled in execution time. New mobile devices that use GPU will be much faster and energy-efficient than their processor-only counterparts. This article at Tom's Hardware shows how OpenCL is evolving, how it will reach future software developments and current implications. This very interesting article highlights facts that display how high an impact GPGPU computing has, such as: Nikola Bozinovic from MotionDSP
"(...) an off-the-shelf laptop you buy for $600 is going to give you the performance of a $2000 desktop from before the heterogeneous computing era, just because you didn't have the power of parallel computing at your fingertips."
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