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toshikaz55 2008/07/30
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ç¾åœ¨ï¼ŒGPGPUã¨æ•°å€¤è¨ˆç®—ã«é–¢ã™ã‚‹ç ”ç©¶ã‚’ã—ã¦ã„ã¾ã™ï¼Ž ã“ã®ãƒšãƒ¼ã‚¸ã§ã¯ï¼Œç ”ç©¶ã«é–¢ã™ã‚‹æƒ…å ±ãƒ¼ç‰¹ã«GPGPUãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ã«é–¢ã™ã‚‹æƒ…å ±ã‚’è¨˜è¿°ã—ã¦ã„ã¾ã™ï¼Ž è‰²ã€…ã¨å®Ÿè£…ä¸ã«ã¤ãã€ãƒšãƒ¼ã‚¸ã®æ›´æ–°ã¯æ»žã£ã¦ã„ã¾ã™ã€‚WebForumãªã©ã§èžã„ã¦ã„ãŸã ã‘ã‚Œã°ã‚ã‚‹ç¨‹åº¦ã®æƒ…å ±ã¯æä¾›ã§ãã‚‹ã¨æ€ã„ã¾ã™ãŒâ€¦â€¦ã€‚ GPGPUã¨ã¯ GPUã«ã‚ˆã‚‹æ•°å€¤è¨ˆç®— DirectXã«ã‚ˆã‚‹å®Ÿè£…æ–¹æ³• OpenGLã«ã‚ˆã‚‹å®Ÿè£…æ–¹æ³• CPUã¨GPUã‚’ç”¨ã„ãŸãƒ‡ãƒ¼ã‚¿ä¸¦åˆ—å‡¦ç† è¤‡æ•°ã®GPUã‚’åˆ©ç”¨ã™ã‚‹æ–¹æ³•ã«ã¤ã„ã¦ CUDAã«æ‰‹ã‚’å‡ºã—ã¦ã¿ã‚‹ ãƒªãƒ³ã‚¯ GPGPUã¨ã¯ é«˜æ©Ÿèƒ½åŒ–ã—ãŸGPUã‚’ç”¨ã„ã¦ï¼Œæ§˜ã€…ãªå‡¦ç†ã‚’è¡Œã†ã“ã¨ï¼Žå¯¾è±¡åˆ†é‡Žã¯ç…§æ˜Žå‡¦ç†ï¼Œé™°å½±å‡¦ç†ï¼Œãƒã‚¹ãƒˆã‚¨ãƒ•ã‚§ã‚¯ãƒˆï¼Œã‚·ãƒŸãƒ¥ãƒ¬ãƒ¼ã‚·ãƒ§ãƒ³ï¼Œæ•°å€¤è¨ˆç®—ãªã©å¤šå²ã«ã‚ãŸã‚‹ï¼Ž GPUã«ã‚ˆã‚‹æ•°å€¤è¨ˆç®— GPUã§æ•°å€¤è¨ˆç®—å•é¡Œã‚’è§£ãï¼Ž GPUã«ã‚ˆã‚‹æ•°å€¤è¨ˆç®—ã‚’å‚ç…§ DirectXã«ã‚ˆã‚‹å®Ÿè£…æ–¹æ³• DirectXã«ã‚ˆã‚‹å®Ÿè£…æ–¹æ³•ï¼šGPUã«ã‚ˆã‚‹æ•°
toshikaz55 2008/04/21
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Developer
Welcome to the GPGPU.org Developer Resources page. Here you will find a wealth of information on the GPGPU programming, including tutorials, utility code, examples, useful links and much more. All of the code here is open source. Jump to GPGPU Programming Conference Tutorials Recommended Reading Material GPGPU Programming The GPGPU programming landscape has rapidly evolved over the past several ye
toshikaz55 2008/04/11
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é«˜æ ¡ç”Ÿã®ãŸã‚ã® NVIDIA CUDA ã‚µãƒžãƒ¼ã‚ãƒ£ãƒ³ãƒ— 2012 8/30 thu. | NVIDIA
CUDA Zone CUDAÂ® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU â€“ which is optimized for single-threaded performance
toshikaz55 2008/04/11
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akihiko.shirai.as - B-Wiki - GPGPU_JapaneseTranslation
toshikaz55 2008/02/05
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