NVIDIA TESLA Volta V100 32GB PCIe GPU Accelerator Card
32GB PNY NVIDIA Tesla V100, PCIe 3.0 (x16), Volta V100, 5120 CUDA + 640 Tensor Cores, ECC HBM2, 14 TF SP, 7 TF DP
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NVIDIA® Tesla® V100 is the world’s most advanced data center GPU ever built to accelerate AI, HPC, and graphics. Powered by NVIDIA Volta™, the latest GPU architecture, Tesla V100 offers the performance of up to 100 CPUs in a single GPU—enabling data scientists, researchers, and engineers to tackle challenges that were once thought impossible.
Tesla V100 is the flagship product of Tesla data center computing platform for deep learning, HPC, and graphics. The Tesla platform accelerates over 450 HPC applications and every major deep learning framework. It is available everywhere from desktops to servers to cloud services, delivering both dramatic performance gains and cost savings opportunities.
NVIDIA VOLTA: The New GPU Architecture, Designed to Bring AI to Every Industry
The Core of AI
AI is not defined by any one industry. It exists in fields of supercomputing, healthcare, financial services, big data analytics, and gaming. It is the future of every industry and market because every enterprise needs intelligence, and the engine of AI is the NVIDIA GPU computing platform.
NVIDIA Volta™ is the new driving force behind artificial intelligence. Volta will fuel breakthroughs in every industry. Humanity’s moonshots like eradicating cancer, intelligent customer experiences, and self-driving vehicles are within reach of this next era of AI.
640 Tensor Cores: An Exponential Leap in Performance
Every industry needs AI, and with this massive leap forward in speed, AI can now be applied to every industry. Equipped with 640 Tensor Cores, Volta delivers over 100 Teraflops per second (TFLOPS) of deep learning performance, over a 5X increase compared to prior generation NVIDIA Pascal™ architecture.
New GPU Architecture: Engineered for the Modern Computer
Humanity’s greatest challenges will require the most powerful computing engine for both computational and data science. With over 21 billion transistors, Volta is the most powerful GPU architecture the world has ever seen. It pairs NVIDIA® CUDA® and Tensor Cores to deliver the performance of an AI supercomputer in a GPU.
Volta-Optimized Software: GPU-Accelerated Frameworks and Applications
Data scientists are often forced to make trade-offs between model accuracy and longer run-times. With Volta-optimized CUDA and NVIDIA Deep Learning SDK libraries like cuDNN, NCCL, and TensorRT, the industry’s top frameworks and applications can easily tap into the power of Volta. This propels data scientists and researchers towards discoveries faster than before.
Supports Every Deep Learning Framework:
• Microsoft Cognitive Toolkit
Supports 450+ GPU-Accelerated Applications Including:
• ANSYS Fluent
• Simulia Abaqus
• WRF Features Volta Architecture
By pairing CUDA Cores and Tensor Cores within a unified architecture, a single server with Tesla V100 GPUs can replace hundreds of commodity CPU servers for traditional HPC and Deep Learning.
Equipped with 640 Tensor Cores, Tesla V100 delivers 120 TeraFLOPS of deep learning performance. That’s 12X Tensor FLOPS for DL Training, and 6X Tensor FLOPS for DL Inference when compared to NVIDIA Pascal™ GPUs.
Maximum Efficiency Mode
The new maximum efficiency mode allows data centers to achieve up to 40% higher compute capacity per rack within the existing power budget. In this mode, Tesla V100 runs at peak processing efficiency, providing up to 80% of the performance at half the power consumption.
With a combination of improved raw bandwidth of 900 GB/s and higher DRAM utilization efficiency at 95%, Tesla V100 delivers 1.5X higher memory bandwidth over Pascal GPUs as measured on STREAM.
Tesla V100 is architected from the ground up to simplify programmability. Its new independent thread scheduling enables finer-grain synchronization and improves GPU utilization by sharing resources among small jobs.
|Graphics Chipset||NVIDIA Tesla V100|
|Manufacturing process||12 nm|
|GPU Name||1x GV100|
|Cores & Clocks|
|NVIDIA CUDA Cores||5120|
|Boost Clock||1370 MHz|
|Video Memory (VRAM)|
|Memory Size||32 GB|
|Memory Clock||1750 MHz|
|Memory Bit Rate||4096 Bit|
|Memory Bandwidth||900 GB/s|
|I/O & Connectivity|
|Interface||PCIe 3.0 (x16)|
|Interface Bandwidth||32 GB/s|
|Multi GPU Support||Supported|
|NVLink Support||Upto 2x Quadro GV100 GPUs via NVLink|
|Total NVLink Bandwidth||N/A|
|Microsoft DirectX Support|
|Multi Monitor Support|
|H.264 1080p30 Streams||N/A|
|Maximum Digital Resolution||N/A|
|Maximum VGA Resolution||N/A|
|Supported Graphics APIs|
|Supported Compute APIs||
|Single Precision (FP32) Processing||Yes|
|Single Precision (FP32) Performance||14 teraFLOPS|
|Double Precision (FP64) Processing||Yes|
|Double Precision (FP64) Performance||7 teraFLOPS|
|Deep Learning (Tensor) Performance||112 teraFLOPS|
|NVIDIA Tensor Cores||640|
|Integer Operations (INT8)|
|NVIDIA RT Cores|
|Power & Thermals|
|Graphics Card Power Connectors||1 x 8-pin PCIe|
|Board Power||250 W|
|Minimum Recommended PSU|
|Maximum GPU Temperature|
|Form Factor||Dual Slot|
|Low Profile Compatible||No|
|Low Profile Support||N/A|
|Dimensions||267. 7 x 111.15 mm|
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- 36 months
- DOA Period:
- 7 days
Date Issued: 2nd Dec 2010
NVIDIA® CUDA parallel computing architecture is enabled on GeForce, Quadro, and Tesla products. Whereas GeForce and Quadro are designed for consumer graphics and professional visualization respectively, the NVIDIA® Tesla™ product family is designed ground-up for parallel computing and offers exclusive computing features.
Date Issued: 8th Oct 2010
Modern desktop computers and notebooks comprise of a CPU, motherboard, graphics, storage, and, usually an optical drive. Computers have a number of ports and sockets that enable the user to plug-in various peripherals such as a printer, USB mouse, or, perhaps most importantly of all, an Internet connection.
Date Issued: 22nd Oct 2008
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Date Issued: 20th Oct 2008
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Date Issued: 20th Oct 2008
Explaining how a modern GPU works in completeness would take a book. Or two. Per class of chip. Per vendor. They’re extraordinarily complex pieces of engineering and production, and the end result contains more transistors than multiple modern x86 processors.
Date Issued: 25th Jun 2008
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Date Issued: 14th Jun 2008
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