2022-04-01ãã1ã¶æéã®è¨äºä¸è¦§
4æã29æ¬ã(å ãã¢ãã¾ã³ãã©ã¤ã ã¯1æ¬ãYoutubeã§1æ¬) 3æã28æ¬ã(å ãã¢ãã¾ã³ãã©ã¤ã ã¯3æ¬) 2æã34æ¬ 1æã42æ¬ã(å ãã¢ãã¾ã³ãã©ã¤ã ã¯6æ¬) 1æ-3æã¾ã§ã®åè¨ : 104æ¬ ãªãã«ã»ã·ã³ã°ã¹ (2021) /THE LITTLE THINGSããã³ã¼ã«ã»ã¯ã·ã³ãã³ä¸»æ¼(å â¦
ã¯ããã« ãã¼ã¨ãã¢ãã¾ã³ã®ã»ããç©ãªã¹ãã«å ¥ãã¨ããã¨ãã¬ã¼ã»Hã»ã·ã£ã¤ã³ã® åããããæè¡ è¬èãªãªã¼ãã¼ã·ãã ãèªã¿ã¾ããã ãã¨ä¸åã 人ãå©ããã¨ã¯ã©ããããã¨ã ãèªããã¨æã£ã¦ãã¾ããèªã¿çµããããããã«è¿½å ãã¾ãã ãåããããæâ¦
ã¯ããã« NVIDIA A100ã«ã¦ãL2 Cacheã®æ§æãå¤ãã£ããã¨ã¯ãä¸è¨ã®ããã°ã§æ¸ãã¾ããã vengineer.hatenablog.com ä»åã¯ãL2 Cache ã®ãµã¤ãºããP100ã®4MBãV100ã®6MBãã A100 ã§ã¯ 40MB (48MB)ãH100 ã§ã¯ 50MB (60MB) ã«ãªã£ã¦ããã®å©ç¨ã«ã¤ãã¦èª¿ã¹â¦
ã¯ããã« NVIDIA Research ã®ãµã¤ããçºãã¦ããããè¦ã¤ãã¾ããã IPA: Floorplan-Aware SystemC Interconnect Performance Modeling and Generation for HLS-based SoCs SystemC ãã¼ã¹ã® Floorplanãæèããã¤ã³ã¿ã¼ã³ãã¯ãã»ããã©ã¼ãã³ã¹ã»ã¢ãã«ã«â¦
ã¯ããã« ãã®ããã°ã§ Esperanto ãåãä¸ããã®ããããªãæã§ã2016.12.07ã§ãããã5年以ä¸åã§ãã vengineer.hatenablog.com CEOã¯Transmetaã®President & CEO ã ã£ã Art Swift ãããFounder and Execute Chairman 㯠Transmeta ã® Founder and CEO â¦
ã¯ããã« NVIDIAã®L2 Cacheã®æ§æã GA100(A100)ã§å¤ãããGH100(H100)ã§ãåãæ§æã«ãªã£ã¦ããã®ã¯ããã®ããã°ã«ãã¢ãããã¾ããã GH100(H100)ã®æ¬¡(Blackwell : GB100)ã«ãªã£ããããããããããL3 Cache ãæå ¥ãããããããã¾ããã å度ãGPU Domaâ¦
ã¯ããã« NVIDIA A100 ãã L2 Cache ã®æ§æãå¤ãã£ãããã§ãã L2 Cache ã®æ§æ NVIDIA GV100(Volta) ã® L2 Cache ã¯ãä¸è¨ã®ããã«ãªã£ã¦ãã¾ããVolta Architecture Whitepaperã®Page 17 ãã説æã®ããã«å¼ç¨ãã¾ãã ä¸è¨ã®ããã«ã6ã¤ã® GPC ã«å¯¾ãâ¦
ã¯ããã« GeForce ç¨GPUã® die size ãæ¯ã¹ã¦ã¿ããã¨æãã¾ãã GPU Specs Database ããè²ã ã¨æ¯è¼ãã¦ã¿ã¾ããã TuringãAmpereãAda Lovelace Turing : TU102 Ampere : GA102 Ada Lovelace : AD102 ããããã©ã¤ã³ã§ãããã£ãããªä»æ§ã§ãã ã¡ã¢ãªã â¦
ã¯ããã« NVIDIAã®NVLINKãP100ã§åãã¦å°å ¥ãããV100ãA100ãH100ã®è»¢éã¬ã¼ããä¸ãã¦ãã¦ãã¾ãã ããã§ãNVLINKã¨ã¯ãä½ãï¼ãæ¯ãè¿ãããã¨æãã¾ãã NVLINKã¨ã¯ï¼ NVLINKã¯ãP100ã®æã«å°å ¥ããã¾ããã NVIDIA Tesla P100 White Paperã®NVLink Hiâ¦
ã¯ããã« ä½æ°ãªãã次ã«èªãæ¬ãã¢ãã¾ã³ã§ç©è²ãã¦ããããåºã¦ãããã¢ãã ã»ã°ã©ã³ãã®æ°ä½ãThink Again ã Kindle ã§è²·ã£ã¦ãèªã¿ã¾ããã www.amazon.co.jp ããã¢ãã ã»ã°ã©ã³ãã£ã¦ã誰ï¼ãã㨠Take & Giveã®èè ã§ããTake & Giveã¯ãåæ¸ã®Kindlâ¦
ã¯ããã« å æ¥ã®NVIDIAã¸ã®ã¢ã¿ãã¯ã«ãã£ã¦ãªã¼ã¯ãããæ å ±ã®ä¸ã«ãGH202 ãªããã®ããããã¨ãç¥ãã¾ãããGB100 ã GB202 ãããããã§ãã wccftech.com GH100 ã¯ãå æ¥ã«çºè¡¨ããã£ã H100 ã®ã·ãªã³ã³ãGH202 ã¯ã¾ã çºè¡¨ããã¦ãã¾ããããä½ãåºã¦ãâ¦
ã¯ããã« NVIDIA Ada Lovelace ã«ã¤ãã¦ã¯ã4.8ã«æ¸ãã¾ããããdie shot ãééã£ã¦ãã¾ãããTuring ã§ããã vengineer.hatenablog.com SemiAnalysis ã®è¨äº semianalysis.substack.com www.youtube.com ãã®è¨äºã®ä¸ã® Ampere (GA10x : Samsung 8N) 㨠Aâ¦
ã¯ããã« æ¨æ¥ã®åå°ä½ãããéè«ã¯ããCache dieã®ç©å±¤ãã«ã¤ãã¦ãã話ãã¾ããã æ¯é±æ¥ææ¥ã®11:00-12:00ã«åå°ä½ãããã«é¢ããéè«ããã£ã¦ãã¾ã第35åãæ¥é±æ¥ææ¥(4/17)ã®åå°ä½ãããéè«Cache dieã®ç©å±¤ã«ã¤ãã¦ãã°ãã°ãã話ãããã¨æã£ã¦ãã¾â¦
ã¯ããã« ããã¨ã«ã»ã«ã¼ããã³ã®ãNOISEããèªã¿çµããã®ã§ãä½ãï¼èªããã®ãªãããªï¼ã¨ Amazon ãçºãã¦ãããè¦ã¤ãããLearn Betterãããã¤ãã®ããã« Kindle çãè²·ãã¾ãã Amazon : Learn Better â é ã®ä½¿ãæ¹ãå¤ãããå¦ã³ãæ·±ã¾ã6ã¤ã®ã¹ããã â¦
ã¯ããã« 2021å¹´4æã® GTC 2021ã«ã¦çºè¡¨ããã£ãGraceããã®Graceã¨Ampere Nextãã¼ã¹ã®DGXã¯ãDGX A100ã®10åã«ãªãã¨ããçºè¡¨ãããã¾ããã cloud.watch.impress.co.jp NVIDIAã«ããã°ã1å ãã©ã¡ã¼ã¿ã¨ããé常ã«è¤éã§å·¨å¤§ãªAIã¢ãã«ãå©ç¨ããã¨ãå¦ç¿â¦
ã¯ããã« Intel ã® HPCç¨GPUãPonte Vecchioããã®ããã°ã§ãåãä¸ãã¦ãã¾ãã vengineer.hatenablog.com æ°ããè³æã¨åç HPC User Forum ã§ã®è¬æ¼è³æï¼Ponte Vecchio: A Multi-Tile 3D Stacked Processor for Exascale Computing The Huge Endeavor toâ¦
ã¯ããã« Ampere Computingã«ã¤ãã¦ã¯ãä¸è¨ã®ããã«ãã®ããã°ã§ãä½åº¦ãåãä¸ãã¾ãããæ¨æ¥ã®ããã°ã®æå¾ã«è¿½è¨ãã¾ããããã©ããã IPOã®æºåããã¦ããããã§ãã vengineer.hatenablog.com vengineer.hatenablog.com ãã®ãã¤ã¼ãã§ç¥ãã¾ãã Ampeâ¦
ã¯ããã« Apple Mac Studioã®M1 Ultraçã $3,999ãã«(ãã ããGPUã¯48ã³ã¢ã§ãã64ã³ã¢ç㯠+$1,000)ããã¾ããæ¥æ¬ã§ã¯ã499,800åã§ã(125å/1ãã«ï¼ï¼ CPUã¯20ã³ã¢ã§ããã8 x 2ã³ã¢ + 2 x 2ã³ã¢ã®æ§æã«ãªã£ã¦ãããã§ããããã¨ãããã¨ã¯ã Ampere Coâ¦
ã¯ããã« AMDãMilanã®CCDã®ä¸ã«L3 Cache silicon dieãç©å±¤ãã32MB + 64MB ã® L3 ãæè¼ãã Milan-Xãªããã®ãçºè¡¨ãã¦ãã¾ãã cloud.watch.impress.co.jp ãã®çºè¡¨ãæåã«èããæãCacheã£ã¦ç©å±¤ã§ãããã ã¨æãã¾ããã Milanã«ã¯ãCCDã8åæè¼ãâ¦
ã¯ããã« AMD EPYC Genoaã®å®ç©åçãè²ã åºã¦ãã¾ããã Genoa ã¯ã12 x CCD + IO ä¸ã®åçã¯ãAMD EPYC 7004 âGenoaâ which has been pictured, features twelve Zen4 chipsetsãã説æã®ããã«å¼ç¨ãã¦ãã¾ããããªãã¢ãã¯ã£ã½ãã§ããã Another AMD EPâ¦
ã¯ããã« ããã¨ã«ã»ã«ã¼ããã³ã®åä½ããã¡ã¹ãï¼ã¹ãã¼ã®Kindleçãè³¼å ¥ããã®ã¯ã2013å¹´8æã§ãããããããã®ããããKindle使ã£ã¦ãããã ãã ç¾å¨ã®Kindleçã®ä¾¡æ ¼ã¯752åï¼752åã§ãã確ããã®é ã¯ãæ庫ãããªãã£ãã®ã§ããã£ã¨é«ãã£ãæ°ããã¾ãâ¦
ã¯ããã« NVIDIAã®ã³ã³ã·ã¥ã¼ãã¼ç¨GPUãAda Lovelace (GeForce RTX 4000ã·ãªã¼ãº) wccftech.com AD102 AD102 ã Ampere ã® GA102 ã«ç¸å½ããã AD102 : RTX 4090/4080ã144 SMãGDDR7 ä¸è¨ã®è¨äºã§ã¯ãH100ã® die shot ã¨ãããã®ãæ²è¼ããã¦ãã¾ãã www.â¦
ã¯ããã« ArmãArmv9ã®CPUã³ã¢ãX2ãA710ãA510ãã¢ãã¦ã³ã¹ããã®ãã2021å¹´ï¼æ news.mynavi.jp ããããArmv9ãªCPUã³ã¢ãæè¼ããã¹ããç¨SoCã¨ãã¦ã¯ã Qualcomm Snapdragon 8 Gen1 Samsung Exynos2200 Mediatek Dimensity 9000 Qualcomm Snapdragin 8 Gâ¦
ã¯ããã« Twitterã«æµãã¦ãããã®ãã¤ã¼ã Qualcommã®æ¨è«ç¨ããããCloud AI100ãMetaã®ã·ã¹ãã å ã§ä½¿ããã¦ããªãããã§ãã This is why the AI100 has disappeared from $QCOM's presentations.Great hardware doesn't matter much without the softwaâ¦
ã¯ããã« AMDãDPUã®Pensandoãè²·åããããã§ãã Pensandoã¨ããä¼ç¤¾ç¥ããªãã£ãã§ãã Pensando ãã®è¨äºã«è©³ããæ¸ãã¦ããã¾ãã www.servethehome.com ãã®è¨äºã®ä¸ã®ä¸å³(Hotchipsã§ã®ãããªã®ã·ã¼ã³ã®ããã§ã)ã説æã®ããã«å¼ç¨ãã¾ãã 2018 : 1â¦
ã¯ããã« ntel ã® iGPUãintel ARC A-Series ä¸è¨ã®å³ã¯ã説æã®ããã«ä¸è¨ã®Youtubeã®2:10ã®ã¨ããããã£ããã£ãããã®ã§ãã www.youtube.com intel ARC A-Series : codename Alchemist ACM-G10 Xe-core : 32 Ray Tracing Units : 32 L2 Cache : 16MB GDDâ¦
ã¯ããã« ã³ã³ã·ã¥ã¼ãã¼ç¨ã®GPUãAMDãNVIDIAãIntelã®æ¯è¼ããã°ã©ããTwitterã«ã¢ããããã¾ããã GPU manufacturing comparison - die size, transistor count and transistor density of current Gen AMD, NVIDIA and Intel GPUs. pic.twitter.com/C1Pâ¦
ã¯ããã« NVIDIA ã® DGX Station ãA100ã使ã£ãã®ã¯ãDGX station A100ããã¼ã¿ã·ã¼ãã¯ããã¡ãã 説æã®ããã«ãã·ã¹ãã ä»æ§ã®ã¨ãããç»åã¨ãã¦å¼ç¨ãã¾ãã æ¶è²»é»åã¯ã1.5kW ãA100 SMX ã ã¨ã400Wã§ãã4åã§1600Wãªãã1.5kW è¶ ãã¾ããCPU(AMD Eâ¦