![]() It does so by improving the performance of existing precisions and bringing new precisions-TF32, INT8, and FP64-that accelerate and simplify AI adoption and extend the power of NVIDIA Tensor Cores to HPC. The NVIDIA Ampere architecture builds upon these innovations by providing up to 20x higher FLOPS for AI. First introduced in the NVIDIA Volta architecture, NVIDIA Tensor Core technology has brought dramatic speedups to AI training and inference operations, bringing down training times from weeks to hours and providing massive acceleration to inference.Whether using MIG to partition an A100 GPU into smaller instances, or NVLink to connect multiple GPUs to accelerate large-scale workloads, the A100 easily handles different-sized application needs, from the smallest job to the biggest multi-node workload. A100 accelerates workloads big and small.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, while allowing IT to optimize the utilization of every available A100 GPU. 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.Ī100 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. As the engine of the NVIDIA data center platform, A100 provides up to 20x higher performance over the prior NVIDIA Volta generation. The NVIDIA A100 80GB Tensor Core GPU delivers unprecedented acceleration-at every scale-to power the world’s highest performing elastic data centers for AI, data analytics, and high-performance computing (HPC) applications. Yes, GP100 looks impressive at first sight, but not so much if you look at what the competition is doing.NVIDIA A100 80GB Unprecedented Acceleration for World’s Highest-Performing Elastic Data Centers A bit slower, but with integrated fabric, option to use as standalone CPU and/or as accelerator(s), option to add DDR4 on 6 channels, with more flexibility. Also by Intel, they released Knight's Landing today. If they continue that with Vega, Nvidia might finally feel some pressure. GP100 is too slow for graphics, that's what they need GP102 for.ĪMD used to get the best balance seen yet with Hawaii. Before, the chips could be used for both, hpc and real time graphics/gaming, this is now over. And no, this efficiency discrepancy is new for nvidia, as the creation of a pure hpc chip is. They're designed for precision and reliability, and that comes at the cost of efficiency and speed.I do know what those products are for. But also, you'll find that most enterprise level hardware has relatively poor performance-per-watt. The Tesla K80, for example, is $5000 and doesn't have any fans (meaning it requires a special case with special cooling) or display connectors. They're designed for precision and reliability, and that comes at the cost of efficiency and speed.Īs stated by tuke81, Teslas aren't meant for consumers. Comparison will be interesting.As stated by tuke81, Teslas aren't meant for consumers. I'm curious if AMD can reach double FP16 performance with Vega as well. did not really result in drawbacks for consumers/those relying on FP32. So almost pure consumer card, which is also more suitable for fp32 needs.įor Hawaii, half FP64 perf. GP102 might be similar to gm200 vs gm204: same dp/sp ratio as gp104, smaller die size and higher clocked than gp100(maybe even gddr5x and obviously no nvlink). Nvidia might do some little tweaks for it to get power consumption down and clocks higher and maybe re-release it as gp200 or just keep it as it's and put all effort to Volta). Comparison will be interesting.Yeah I don't think gp100 will ever come to consumer space, it's looks like pure hpc chip(there's not even fully enabled gp100 out there. But this seems to confirm the rumors about upcoming GP102.įor Hawaii, half FP64 perf. Sure, it has other improvements like NVLink - which you can't even make use of on this PCIe card. The big chips should actually be more efficient, and it does even use HBM.ĭouble FP16, half FP64 performance at the same time seems to cost them much. 9.3 TFLOPs, GP104 does almost reach that with much lower power draw (it does reach it with OC and still less power). For me, GP100 remains a bit of a disappointment.
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