High-Performance GPU Computing in the Julia Programming Language | NVIDIA Technical Blog
High-Performance GPU Computing in the Julia Programming Language Julia is a high-level programming language for mathematical computing that is as easy to use as Python, but as fast as C. The language has been created with performance in mind, and combines careful language design with a sophisticated LLVM-based compiler [Bezanson et al. 2017]. Julia is already well regarded for programming multicor
Hands-on: Turbo charge your MacBook Pro graphics performance with the Akitio Node eGPU over Thunderbolt 3 [Video] - 9to5Mac
The Node features a cover that slides on to the unit a little awkwardly, but it does a good job of protecting the internals and providing airflow to the internals. Both the front and rear of the Node feature perforated panels to allow plenty of cool air to work its way throughout the case. With a graphics card inside, the Node is pretty heavy, almost like a small PC case. The unit’s handle is obvi
![Hands-on: Turbo charge your MacBook Pro graphics performance with the Akitio Node eGPU over Thunderbolt 3 [Video] - 9to5Mac](https://cdn-ak-scissors.b.st-hatena.com/image/square/52b9241911d6b4425b61da8f1d97f85360a1439a/height=288;version=1;width=512/https%3A%2F%2F9to5mac.com%2Fwp-content%2Fuploads%2Fsites%2F6%2F2017%2F01%2Fakitio-node-rx-480-gpu.jpg%3Fquality%3D82%26strip%3Dall)
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Delivering Performance Leadership for the Data Center AMD Instinct™ accelerators are engineered from the ground up for this new era of data center computing, supercharging HPC and AI workloads to propel new discoveries. The AMD Instinct™ family of accelerators can deliver industry leading performance for the data center at any scale from single server solutions up to the world’s largest supercompu
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MacOSX 10.11.1 El Capitanã«ã¦GPUã‚’Thunderbolt経由ã§èªè˜ã•ã›ã‚‹æ–¹æ³•ã‚’記ã—ã¾ã™ã€‚ El Capitanã§ã¯kextファイルã®ã‚ˆã†ãªã‚·ã‚¹ãƒ†ãƒ ファイルを容易ã«æ›¸ãæ›ãˆã‚‹äº‹ãŒåŽ³ã—ããªã‚Šã¾ã—ãŸã€‚ ã“ã“ã§ã¯ãã®å›žé¿æ–¹æ³•ã‚’記ã—ã¾ã™ã€‚ ----å¿…ãšãƒãƒƒã‚¯ã‚¢ãƒƒãƒ—ã‚’å–り作æ¥ã«ã¤ã„ã¦ã¯è‡ªå·±è²¬ä»»ã§ãŠã“ãªã£ã¦ãã ã•ã„!---- Step.1) Command-Rを押ã—ãªãŒã‚‰Mac ã‚’å†èµ·å‹•ã€‚ 「ユーティリティã€ãƒ¡ãƒ‹ãƒ¥ãƒ¼ã‹ã‚‰ã€Œã‚¿ãƒ¼ãƒŸãƒŠãƒ«ã€ã‚’èµ·å‹•ã—以下ã®ã‚³ãƒžãƒ³ãƒ‰ã‚’実行 csrutil disable é–“é•ã£ã¦ã„ãªã‘ã‚Œã°ã€ŽSuccessfully disabled System Integrity Protection. 〜〜(ç•¥)ã€ã¨ã„ã†ã‚ˆã†ãªãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãŒå‡ºã‚‹ã¯ãšã§ã™ã€‚ ãã®å¾Œå†èµ·å‹•ã—ã¾ã™ã€‚ Step.2) 開発モードを有効ã«ã—ã¾ã™ã€‚ sudo nvram boot-args=â€k
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2015å¹´8月19日　ディープラーニングセミナー2015 åå¤å±‹ãƒ«ãƒ¼ã‚»ãƒ³ãƒˆã‚¿ãƒ¯ãƒ¼ エヌビディアåˆåŒä¼šç¤¾ã€€ã‚·ãƒ‹ã‚¢ãƒ‡ãƒ™ãƒãƒƒãƒ‘ーテクノãƒã‚¸ãƒ¼ エンジニア　æˆç€¬å½° [概è¦] 本講演ã§ã¯ã€ãƒ¢ãƒ«ãƒ•ã‚©ãŒå–り組むDeep Learning（以下ã€DL）ビジãƒã‚¹ã«ã¤ã„ã¦ã®æ¦‚è¦ã¨ã€å®Ÿç”¨åŒ–ã« å‘ã‘ã¦ãƒ‡ã‚£ãƒ¼ãƒ—ラーニングã§ã¯GPU利用ãŒãƒ‡ãƒ•ã‚¡ã‚¯ãƒˆã«ãªã£ã¦ã„ã¾ã™ãŒã€GPUを使ã†ã¨ãªãœãƒ‡ã‚£ãƒ¼ãƒ—ラーニングã®å¦ç¿’ãƒ•ã‚§ãƒ¼ã‚ºã‚’åŠ é€Ÿã§ãã‚‹ã®ã‹ã€ãã®æŠ€è¡“çš„ãªèƒŒæ™¯ãƒ»ç†ç”±ã‚’説明ã™ã‚‹ã¨ã¨ã‚‚ã«ã€ã‚¨ãƒŒãƒ“ディアã®ãƒ‡ã‚£ãƒ¼ãƒ—ラーニング関連ソフトウェアã®æœ€æ–°æƒ…å ±ã‚’ç´¹ä»‹è‡´ã—ã¾ã™ã€‚Read less
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é«˜æ ¡ç”Ÿã®ãŸã‚ã® NVIDIA CUDA サマーã‚ャンプ 2012 8/30 thu. | NVIDIA
CUDA Zone CUDA® 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 – which is optimized for single-threaded performance
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