[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-672780-105":59,"doc-detail-672780-en":129},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":122,"head_meta":124,"extra_data":126,"updated_unix":128},105,"en","nvidia-a100-tensor-core-gpu-datasheet-update","NVIDIA A100 Tensor Core GPU - Datasheet Update","","NVIDIA A100 Tensor Core GPU datasheet highlights unprecedented acceleration for AI, data analytics, and high-performance computing across elastic data centers. It details scaling options including up to seven Multi-Instance GPU (MIG) instances and a unified platform for dynamic workload adjustment. The document emphasizes next-generation tensor core capabilities, doubled 80GB memory, and peak bandwidth up to 2 TB/s. System specifications compare NVLink and PCIe variants, including compute precision modes, throughput, and power targets, along with performance claims across training, inference, and HPC workloads.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":30,"@type":76,"position":81},"https://docshare.wps.com/document/technology/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/nvidia-a100-tensor-core-gpu-datasheet-update/672780/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/nvidia-a100-tensor-core-gpu-datasheet-update/672780.png","ImageObject",300,407,{"name":92,"@type":93},"FajarTechTalk","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-02",true,{"@type":101,"interactionType":102,"userInteractionCount":14},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"What scaling features does NVIDIA A100 support for elastic data centers?","Question",{"text":111,"@type":112},"A100 can be scaled up or partitioned into up to seven isolated GPU instances using Multi-Instance GPU (MIG). This enables dynamic adjustment to changing workload demands.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"How does the datasheet compare A100 80GB with prior generations?",{"text":116,"@type":112},"It states A100 80GB doubles GPU memory and provides the world’s fastest memory bandwidth at 2 TB/s. It also claims up to 20X higher performance over the prior NVIDIA Volta generation.",{"name":118,"@type":109,"acceptedAnswer":119},"What system variants are included in the specifications?",{"text":120,"@type":112},"The document provides system specifications comparing NVIDIA A100 for NVLink and NVIDIA A100 for PCIe, including compute peak values, memory capacity, bandwidth, interconnect, and form factor details.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},672780,1793607185,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":81,"language":138,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":139,"faqs":140,"seo_title":141,"seo_description":67,"update_tm":128,"read_time":39},962094249465,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","NVIDIA A100  \nTENSOR CORE GPU  \nUNPRECEDENTED SCALE AT EVERY SCALE  \nThe Most Powerful Compute Platform for Every Workload  \nThe NVIDIA® A100 Tensor Core GPU delivers unprecedented acceleration—at every scale—to power the world’s highestperforming elastic data centers for AI, data analytics, and high-performance computing (HPC) applications. As the engine of the NVIDIA data center platform, A100 provides up to 20X higher performance over the prior NVIDIA Volta™ generation. A100 can efficiently scale up or be partitioned into seven isolated GPU instances, with Multi-Instance GPU (MIG) providing a unified platform that enables elastic data centers to dynamically adjust to shifting workload demands.  \nNVIDIA A100 Tensor Core technology supports a broad range of math precisions, providing a single accelerator for every workload. The latest generation A100 80GB doubles GPU memory and debuts the world’s fastest memory bandwidth at 2 terabytes per second (TB/s), speeding time to solution for the largest models and most massive data sets.  \nA100 is part of the complete NVIDIA data center solution that incorporates building blocks across hardware, networking, software, libraries, and optimized AI models and applications from NGC™ . Representing the most powerful end-to-end AI and HPC platform for data centers, it allows researchers to deliver real-world results and deploy solutions into production at scale.  \nSYSTEM SPECIFICATIONS  \n\n| NVIDIA A100\u003Cbr>for NVLink |  |  | NVIDIA A100\u003Cbr>for PCIe |\n| --- | --- | --- | --- |\n| Peak FP64 | 9.7 TF |  | 9.7 TF |\n| Peak FP64 Tensor Core | 19.5 TF |  | 19.5 TF |\n| Peak FP32 | 19.5 TF |  | 19.5 TF |\n| Tensor Float 32 (TF32) | 156 TF | 312 TF* |  | 156 TF | 312 TF* |\n| Peak BFLOAT16 Tensor Core | 312 TF | 624 TF* |  | 312 TF | 624 TF* |\n| Peak FP16 Tensor Core | 312 TF | 624 TF* |  | 312 TF | 624 TF* |\n| Peak INT8 Tensor Core | 624 TOPS | 1,248\u003Cbr>TOPS* |  | 624 TOPS | 1,248\u003Cbr>TOPS* |\n| Peak INT4 | 1,248 |  | 1,248 |\n| Tensor Core | TOPS | 2,496 |  | TOPS | 2,496 |\n|  | TOPS* |  | TOPS* |\n| GPU Memory | 40GB | 80GB | 40GB |\n| GPU Memory | 1,555 | 2,039 | 1,555 GB/s |\n| Bandwidth | GB/s | GB/s |  |\n| Interconnect | NVIDIA NVLink |  | NVIDIA NVLink |\n|  | 600 GB/s** |  | 600 GB/s** |\n|  | PCIe Gen4 64 GB/s |  | PCIe Gen4 64 GB/s |\n| Multi-Instance | Various instance |  | Various instance |\n| GPU | sizes with up to |  | sizes with up to |\n|  | 7 MIGs @ 10 GB |  | 7 MIGs @ 5 GB |\n| Form Factor | 4/8 SXM on\u003Cbr>NVIDIA HGX™ A100 |  | PCIe |\n| Max TDP Power | 400 W | 400 W | 250 W |\n\n* With sparsity  \n** SXM GPUs via HGX A100 server boards; PCIe GPUs via NVLink Bridge for up to 2 GPUs  \nNVIDIA A100 | DATAShEET | JAN21 | 1  \nIncredible Performance Across Workloads  \n\n| Up to 3X Higher AI Training on Largest Models\u003Cbr>DLRM Training |  |\n| --- | --- |\n| 3X\u003Cbr>2X\u003Cbr>1X\u003Cbr>0 | |\n| DLRM on HugeCTR framework, precision = FP16 | NVIDIA A100 80GB batch size = 48 | NVIDIA A100 40GB batch size = 32 | NVIDIA V100 32GB batch size = 32. |  |\n\n\n| Up to 249X Higher AI Inference Performance over CPUs\u003Cbr>BERT-LARGE Inference |  |\n| --- | --- |\n| 250X\u003Cbr>200X\u003Cbr>150X\u003Cbr>100X\u003Cbr>50X\u003Cbr>0 | 245X 249X 1X\u003Cbr>\u003Cbr>|\n| CPU Only A100 40GB A100 80GB\u003Cbr>Sequences Per Second-Relative Performance\u003Cbr>BERT-Large Inference | CPU only: Dual Xeon Gold 6240 @2.60 GHz, precision = FP32, batch size = 128 | V100: NVIDIA TensorRT™ (TRT) 7.2, precision = INT8, batch size = 256 | A100 40GBand 80GB, batch size = 256, precision = INT8 with sparsity. |  |\n\n\n| 11X More HPC Performance in Four Years Throughput for Top HPC Apps |  |  |  |  |  |\n| --- | --- | --- | --- | --- | --- |\n| 11X\u003Cbr>10X\u003Cbr>9X\u003Cbr>8X\u003Cbr>7X\u003Cbr>6X\u003Cbr>5X\u003Cbr>4X\u003Cbr>3X\u003Cbr>2X\u003Cbr>1X\u003Cbr>0 | 11X 4X 3X 2X \u003Cbr>1X\u003Cbr>\u003Cbr>\u003Cbr>\u003Cbr>|  |  |  |  |\n|  | P100\u003Cbr>2016 | V100\u003Cbr>2017 | V100\u003Cbr>2018 | V100\u003Cbr>2019 | A100\u003Cbr>2020 |\n| Throughput-Relative Performance\u003Cbr>Geometric mean of application speedups vs. P100: Benchmark application: Amber [PME-Cellulose_NVE], Chroma [szscl21_24_ 128], GROMACS [ADH","cbCail9LNotBd6uk","https://ap.wps.com/l/cbCail9LNotBd6uk","pdf",878484,"English","# System Specifications\n## NVIDIA A100 for NVLink vs NVIDIA A100 for PCIe\n# Incredible Performance Across Workloads\n## AI Training\n## AI Inference vs CPUs\n## HPC Performance\n## RNN-T Inference\n## Quantum Espresso\n## Big Data Analytics Benchmark\n# Groundbreaking Innovations\n## NVIDIA Ampere Architecture\n## Third-Generation Tensor Cores","[{\"question\":\"What scaling features does NVIDIA A100 support for elastic data centers?\",\"answer\":\"A100 can be scaled up or partitioned into up to seven isolated GPU instances using Multi-Instance GPU (MIG). This enables dynamic adjustment to changing workload demands.\"},{\"question\":\"How does the datasheet compare A100 80GB with prior generations?\",\"answer\":\"It states A100 80GB doubles GPU memory and provides the world’s fastest memory bandwidth at 2 TB/s. It also claims up to 20X higher performance over the prior NVIDIA Volta generation.\"},{\"question\":\"What system variants are included in the specifications?\",\"answer\":\"The document provides system specifications comparing NVIDIA A100 for NVLink and NVIDIA A100 for PCIe, including compute peak values, memory capacity, bandwidth, interconnect, and form factor details.\"}]","NVIDIA A100 Tensor Core GPU - Datasheet Update | PDF"]