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CUDAã«é–¢ã™ã‚‹ryochackã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (4)

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CUDAã§ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ã™ã‚‹å‰ã«ã‚„ã£ã¦ãŠããŸã„ã“ã¨ - æ ªå¼ä¼šç¤¾CFlatã®æ˜Žå¾Œæ—¥ã‚¹ã‚¿ã‚¤ãƒ«ã®ãƒ–ãƒã‚°
ã“ã¡ã‚‰ã®è¨˜äº‹ã‚‚ã”ç¢ºèªä¸‹ã•ã„ã€‚ CUDA6.0ç”¨ã«CPUã¨GPUã®é€Ÿåº¦æ¯”è¼ƒã‚³ãƒ¼ãƒ‰ã‚’ä¿®æ£ - æ ªå¼ä¼šç¤¾CFlatã®æ˜Žå¾Œæ—¥ã‚¹ã‚¿ã‚¤ãƒ«ã®ãƒ–ãƒã‚° GPUã¨CPUã®é€Ÿåº¦æ¯”è¼ƒã‚’ã—ãŸã„ ä»¥å‰CUDAã§ã®ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ãŒå®Œæˆã—ãŸéš›ã«ã€CPUã¨ã®é€Ÿåº¦æ¯”è¼ƒã‚’è¡Œã„ãŸã„ã¨ã„ã†å½“ãŸã‚Šå‰ã®è¦æœ›ãŒä¸ŠãŒã‚Šã¾ã—ãŸã€‚ ãã“ã§GPUã¨CPUã‚’åˆ‡ã‚Šæ›¿ãˆã‚‹ã‚³ãƒ¼ãƒ‰ã‚’ä½œæˆã—ãŸã®ã§ã™ãŒã€ã©ã†ã›ãªã‚‰æœ€åˆã‹ã‚‰ä½œã£ã¦ãŠãã¹ãã ã£ãŸã¨åçœã—ã¾ã—ãŸã€‚ ä»Šå›žã¯ãã®éš›ã«ä½œæˆã—ãŸGPUã¨CPUã®é€Ÿåº¦æ¯”è¼ƒã‚³ãƒ¼ãƒ‰ã‚’å…¬é–‹ã—ã¾ã™ã€‚ OpenMPã®è¨å®š GPUã¨CPUã®é€Ÿåº¦æ¯”è¼ƒã‚’ã™ã‚‹éš›ã«CPUã®æ–¹ã‚‚ä¸¦åˆ—åŒ–ã—ãªã„ã¨ä¸å…¬å¹³ã§ã™ã€‚CPUã®ä¸¦åˆ—åŒ–ã«ã¯è¨å®šãŒç°¡å˜ãªOpenMPã‚’ä½¿ã„ã¾ã™ã€‚ CUDAãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã§OpenMPã‚’ä½¿ç”¨ã§ãã‚‹ã‚ˆã†ã«ã™ã‚‹ã«ã¯ã€ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã®ãƒ—ãƒãƒ‘ãƒ†ã‚£ã‚’é–‹ãã€æ§‹æˆãƒ—ãƒãƒ‘ãƒ†ã‚£/CUDA C/C++/Command Lineã®è¿½åŠ ã‚ªãƒ—ã‚·ãƒ§ãƒ³ã«-Xcompil
ryochack 2014/04/15
CUDA

GPU

performance
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CUDA 6ã®è©±@é–¢è¥¿GPGPUå‹‰å¼·ä¼š#5
8. cudaMallocManaged CPU CUDA Uniï¬ed Memory void sortfile(FILE *fp, int N) { char *data; data = (char *)malloc(N); ! ! ! ! } fread(data, 1, N, fp); qsort(data, N, 1, compare); use_data(data); free(data); void sortfile(FILE *fp, int N) { char *data; cudaMallocManaged(&data, N); ! ! ! ! } fread(data, 1, N, fp); qsort<<<â€¦>>>(data, N, 1, compare); cudaDeviceSynchronize(); use_data(data); cudaFree(data
ryochack 2014/01/20
CUDA6.0æ–°æ©Ÿèƒ½

GPU

CUDA
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CUDA 6é€Ÿå ±(1): Unified Memory - ãƒˆãƒ¼ã‚¿ãƒ«ãƒ»ãƒ‡ã‚£ã‚¹ã‚¯ãƒãƒ¼ã‚¸ãƒ£ãƒ»ã‚µã‚¤ãƒˆï¼ˆäº‹å®Ÿã‚’ã‚ã‚Šã®ã¾ã¾ã«ï¼‰
å…ˆæ—¥ç™ºè¡¨ã•ã‚ŒãŸCUDA 6ã«ã¤ã„ã¦ã€NVIDIAãŒç´¹ä»‹ã—ã¦ã„ã‚‹æ–°æ©Ÿèƒ½ã‚’ã„ãã¤ã‹ç´¹ä»‹ã™ã‚‹ã€‚ãªãŠã€Toolkitã¯ã¾ã è©•ä¾¡ã§ãã‚‹çŠ¶æ…‹ã§ã¯ãªã„ãŸã‚ã€NVIDIAã®ç´¹ä»‹ã‹ã‚‰ã®æŽ¨æ¸¬ã«ã‚ˆã‚‹è¨˜äº‹ã§ã‚ã‚‹ã€‚ãã®ãŸã‚ã€æ£ç¢ºæ€§ã«æ¬ ã‘ã‚‹å¯èƒ½æ€§ã«ã¤ã„ã¦æ°—ã‚’ä»˜ã‘ãŸã„ã€‚ Unified Memoryã¨ã¯ CPUã¨GPUã¨ã®ä¸¡æ–¹ã‹ã‚‰ã‚¢ã‚¯ã‚»ã‚¹ã•ã‚Œã‚‹ã“ã¨ã‚’ç›®çš„ã¨ã—ãŸãƒ¡ãƒ¢ãƒªé ˜åŸŸã§ã‚ã‚‹ã€‚CPUã¨GPUã¨ã®ä¸¡æ–¹ã«ãƒ¡ãƒ¢ãƒªã‚’ç¢ºä¿ã—ã€ãƒ‡ãƒ¼ã‚¿ã®ã‚³ãƒ’ãƒ¼ãƒ¬ãƒ³ã‚·ã‚’ä¿ã¤ã‚ˆã†ã«é©å®œåŒæœŸãŒè¡Œã‚ã‚Œã‚‹ã‚ˆã†ãªå®Ÿè£…ã§ã‚ã‚‹ã¨èª¬æ˜Žã•ã‚Œã¦ã„ã‚‹ã€‚ ã—ã°ã—ã°ã€ŒCPUã¨GPUã®ä¸¡æ–¹ã®ãƒ¡ãƒ¢ãƒªã«ã‚¢ãƒ—ãƒªã‚±ãƒ¼ã‚·ãƒ§ãƒ³ãŒç›´æŽ¥ã‚¢ã‚¯ã‚»ã‚¹ã§ãã‚‹ã‚ˆã†ã«ãªã‚‹ã€ã¨ã„ã†ã‚ˆã†ãªè¡¨ç¾ã§ç´¹ä»‹ã—ã¦ã„ã‚‹ãƒ‹ãƒ¥ãƒ¼ã‚¹ã‚µã‚¤ãƒˆãŒã‚ã‚‹ãŒã€CPUä¸Šã®ãƒ¡ãƒ¢ãƒªã‚’GPUãŒç›´æŽ¥ã‚¢ã‚¯ã‚»ã‚¹ã™ã‚‹æ©Ÿèƒ½ã¯ã™ã§ã«CUDA 2.2ã®ã¨ãã«ã€ŒMapped Memoryã€ã¨ã„ã†æ©Ÿèƒ½ã§å®Ÿç¾ã•ã‚Œã¦ã„ã‚‹ã€‚ã•ã‚‰ã«ã€CUDA 4.0ã®ã¨ãã«å®Ÿè£…ã•ã‚ŒãŸã€Œ
ryochack 2014/01/20
CUDA6.0 "Unified Memory:CPUã¨GPUã¨ã§2é‡ã«ç¢ºä¿ã—ã¦åŒæœŸã‚’è‡ªå‹•çš„ã«è¡Œã†ãƒ¡ãƒ¢ãƒª"

GPU

CUDA
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Unified Memory in CUDA 6 | NVIDIA Technical Blog
With CUDA 6, NVIDIA introduced one of the most dramatic programming model improvements in the history of the CUDA platform, Unified Memory. In a typical PC or cluster node today, the memories of the CPU and GPU are physically distinct and separated by the PCI-Express bus. Before CUDA 6, that is exactly how the programmer has to view things. Data that is shared between the CPU and GPU must be alloc
ryochack 2014/01/20
CUDA6.0ã§ã®Unified Memoryã«ã¤ã„ã¦

GPU

CUDA
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