Re: [Mplapack-devel] Accelerated double-double version of Regmm on NVIDIA C2050
Status: Pre-Alpha
Brought to you by:
nakatamaho
From: Fletcher, J. P <j.p...@as...> - 2011-10-31 11:04:06
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Maho I am attempting to get this code working on my system with a GTX 460 card. At the moment I have a strange problem compiling the code which is a failure to find __builtin_isfinite. This seems to be a problem between gcc 4.4 and the nvcc compiler, which has occurred in a number of projects as well. I have overcome this temporarily by doctoring the isfinite implementation in dd_real.h The other problem is about compatibility of NVIDIA driver versions. I am hopeful of overcoming these as I have MPACK working with qd on my computer, and also code which works with CUDA. I will report further when I have a solution. If anyone else can help, please post a reply. Thank you for this work. John Dr John P. Fletcher Tel: (44) 121 204 3389 (direct line), FAX: (44) 121 204 3678 Chemical Engineering and Applied Chemistry (CEAC), Associate Dean - External Relations, School of Engineering and Applied Science (EAS), Aston University, Aston Triangle, BIRMINGHAM B4 7ET U.K. -----Original Message----- From: Maho NAKATA [mailto:ch...@ma...] Sent: 28 October 2011 01:54 To: mpl...@li... Cc: y-...@jf...; hi...@ri... Subject: [Mplapack-devel] Accelerated double-double version of Regmm on NVIDIA C2050 Hi all, I have just uploded Accelerated double-double version of Regmm on NVIDIA C2050. You can download from here http://sourceforge.net/projects/mplapack/files/mpack/ . more explicitly, http://sourceforge.net/projects/mplapack/files/mpack/Rgemm_C2050_20111026.tar.gz/download the file name is Rgemm_C2050_20111026.tar.gz. This is preliminary version of double-double version Rgemm, for benchmarking purpose. Requirements: * NVIDIA C2050 or C2070. * CUDA 3.2 * SDK assumed to be installed at /usr/local/cuda/. How to test: $ tar xvfz Rgemm_C2050_20111026.tar.gz $ cd Rgemm_C2050 $ make ... building Rgemm for C2050, and taking benchmark and results are saved as CSV files. The default precision for multiplication and addition is rounding IEEE's one. subdir bench_all test square matrix of various size. subdir bench_ecc_onoff test ecc on/off case. change in ECC configuration requires reboot. subdir bench_jitter test jitter of NVIDIA GPU. subdir bench_pointerredirecting test the effect of pointer redirecting. subdir bench_rectangular test matrix-matrix multiplication for rectangular matrix. subdir bench_sloppy test lower accurate methods. How to look at the results: All results are in csv file. For example, please open the "Rgemm_NN_Total_bench.csv" file. This result includes CPU-GPU transfer time (Total), all matrices are not transposed, (NN) and all matrices are square matrices. First five lines can be ignored. Next line shows "2, 0.00007523". This means A, B, and C are 2x2 matrices, and 0.00007523 means 0.00007523 GFlops. Therefore, this csv file's format is "size, Gflops". --quote start device_count : 1 device name -> Tesla C2050 cudareturn -> 0 cudaGetDevice()=0 n - n mode 2, 0.00007523 8, 0.00401315 15, 0.02368548 32, 0.18986460 47, 0.51354554 64, 1.10947988 65, 1.05225521 81, 1.77540829 97, 2.11975457 ... --quote end Notes: The full reference version can be downloaded is http://mplapack.sourceforge.net/, and this version of Rgemm will be integrated hopefully soon. License: 2-clause BSD style license. See each files for details. Citation: *"Acceleration of matrix-matrix product in double-double precision using GPU", Maho NAKATA, Yasuyoshi TAKAO, Shigeho NODA, and Ryutaro HIMENO, Keisankogakukoenkai Ronbunsyuu, Vol. 16. 2011. * "Rgemm-preprint.ja.pdf" is included as well (preprint, in Japanese). Programmed by: Takao, Yasuyoshi, Nakata, Maho, and RIKEN. Enjoy, -- Nakata Maho http://accc.riken.jp/maho/ , JA OOO http://ja.openoffice.org/ http://blog.goo.ne.jp/nakatamaho/ ,GPG: http://accc.riken.jp/maho/maho.pgp.txt ------------------------------------------------------------------------------ The demand for IT networking professionals continues to grow, and the demand for specialized networking skills is growing even more rapidly. Take a complimentary Learning@Cisco Self-Assessment and learn about Cisco certifications, training, and career opportunities. http://p.sf.net/sfu/cisco-dev2dev _______________________________________________ Mplapack-devel mailing list Mpl...@li... https://lists.sourceforge.net/lists/listinfo/mplapack-devel |