NVIDIA H100 80G PCIe
NVIDIA H100 80G PCIe
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Description
An Order-of-Magnitude Leap for Accelerated Computing
Tap into exceptional performance, scalability, and security for every workload with the NVIDIA H100 Tensor Core GPU. With the NVIDIA NVLink™ Switch System, up to 256 H100 GPUs can be connected to accelerate exascale workloads. The GPU also includes a dedicated Transformer Engine to solve trillion-parameter language models. The H100’s combined technology innovations can speed up large language models (LLMs) by an incredible 30X over the previous generation to deliver industry-leading conversational AI.
Supercharge Large Language Model Inference
For LLMs up to 175 billion parameters, the PCIe-based H100 NVL with NVLink bridge utilizes Transformer Engine, NVLink, and 188GB HBM3 memory to provide optimum performance and easy scaling across any data center, bringing LLMs to mainstream. Servers equipped with H100 NVL GPUs increase GPT-175B model performance up to 12X over NVIDIA DGX™ A100 systems while maintaining low latency in power-constrained data center environments.
Ready for Enterprise AI?
Enterprise adoption of AI is now mainstream, and organizations need end-to-end, AI-ready infrastructure that will accelerate them into this new era.
NVIDIA H100 GPUs for mainstream servers come with a five-year subscription, including enterprise support, to the NVIDIA AI Enterprise software suite, simplifying AI adoption with the highest performance. This ensures organizations have access to the AI frameworks and tools they need to build H100-accelerated AI workflows such as AI chatbots, recommendation engines, vision AI, and more.
Securely Accelerate Workloads From Enterprise to Exascale
Up to 4X Higher AI Training on GPT-3
Projected performance subject to change. GPT-3 175B training A100 cluster: HDR IB network, H100 cluster: NDR IB network | Mixture of Experts (MoE) Training Transformer Switch-XXL variant with 395B parameters on 1T token dataset, A100 cluster: HDR IB network, H100 cluster: NDR IB network with NVLink Switch System where indicated.
Transformational AI Training
H100 features fourth-generation Tensor Cores and a Transformer Engine with FP8 precision that provides up to 4X faster training over the prior generation for GPT-3 (175B) models. The combination of fourth-generation NVLink, which offers 900 gigabytes per second (GB/s) of GPU-to-GPU interconnect; NDR Quantum-2 InfiniBand networking, which accelerates communication by every GPU across nodes; PCIe Gen5; and NVIDIA Magnum IO™ software delivers efficient scalability from small enterprise systems to massive, unified GPU clusters.
Deploying H100 GPUs at data center scale delivers outstanding performance and brings the next generation of exascale high-performance computing (HPC) and trillion-parameter AI within the reach of all researchers.
Real-Time Deep Learning Inference
AI solves a wide array of business challenges, using an equally wide array of neural networks. A great AI inference accelerator has to not only deliver the highest performance but also the versatility to accelerate these networks.
H100 extends NVIDIA’s market-leading inference leadership with several advancements that accelerate inference by up to 30X and deliver the lowest latency. Fourth-generation Tensor Cores speed up all precisions, including FP64, TF32, FP32, FP16, INT8, and now FP8, to reduce memory usage and increase performance while still maintaining accuracy for LLMs.
Up to 30X higher AI inference performance on the largest models
Megatron chatbot inference (530 billion parameters)
Projected performance subject to change. Inference on Megatron 530B parameter model based chatbot for input sequence length=128, output sequence length =20 | A100 cluster: HDR IB network | H100 cluster: NVLink Switch System, NDR IB
Up to 7X higher performance for HPC applications
Projected performance subject to change. 3D FFT (4K^3) throughput | A100 cluster: HDR IB network | H100 cluster: NVLink Switch System, NDR IB | Genome Sequencing (Smith-Waterman) | 1 A100 | 1 H100
Exascale High-Performance Computing
The NVIDIA data center platform consistently delivers performance gains beyond Moore’s law. And H100’s new breakthrough AI capabilities further amplify the power of HPC+AI to accelerate time to discovery for scientists and researchers working on solving the world’s most important challenges.
H100 triples the floating-point operations per second (FLOPS) of double-precision Tensor Cores, delivering 60 teraflops of FP64 computing for HPC. AI-fused HPC applications can also leverage H100’s TF32 precision to achieve one petaflop of throughput for single-precision matrix-multiply operations, with zero code changes.
H100 also features new DPX instructions that deliver 7X higher performance over A100 and 40X speedups over CPUs on dynamic programming algorithms such as Smith-Waterman for DNA sequence alignment and protein alignment for protein structure prediction.
DPX instructions comparison NVIDIA HGX™ H100 4-GPU vs dual socket 32-core IceLake.
Accelerated Data Analytics
Data analytics often consumes the majority of time in AI application development. Since large datasets are scattered across multiple servers, scale-out solutions with commodity CPU-only servers get bogged down by a lack of scalable computing performance.
Accelerated servers with H100 deliver the compute power—along with 3 terabytes per second (TB/s) of memory bandwidth per GPU and scalability with NVLink and NVSwitch™—to tackle data analytics with high performance and scale to support massive datasets. Combined with NVIDIA Quantum-2 InfiniBand, Magnum IO software, GPU-accelerated Spark 3.0, and NVIDIA RAPIDS™, the NVIDIA data center platform is uniquely able to accelerate these huge workloads with higher performance and efficiency.
Enterprise-Ready Utilization
IT managers seek to maximize utilization (both peak and average) of compute resources in the data center. They often employ dynamic reconfiguration of compute to right-size resources for the workloads in use.
H100 with MIG lets infrastructure managers standardize their GPU-accelerated infrastructure while having the flexibility to provision GPU resources with greater granularity to securely provide developers the right amount of accelerated compute and optimize usage of all their GPU resources.
Built-In Confidential Computing
Traditional Confidential Computing solutions are CPU-based, which is too limited for compute-intensive workloads such as AI at scale. NVIDIA Confidential Computing is a built-in security feature of the NVIDIA Hopper™ architecture that made H100 the world’s first accelerator with these capabilities. With NVIDIA Blackwell, the opportunity to exponentially increase performance while protecting the confidentiality and integrity of data and applications in use has the ability to unlock data insights like never before. Customers can now use a hardware-based trusted execution environment (TEE) that secures and isolates the entire workload in the most performant way.
Exceptional Performance for Large-Scale AI and HPC
The Hopper Tensor Core GPU will power the NVIDIA Grace Hopper CPU+GPU architecture, purpose-built for terabyte-scale accelerated computing and providing 10X higher performance on large-model AI and HPC. The NVIDIA Grace CPU leverages the flexibility of the Arm® architecture to create a CPU and server architecture designed from the ground up for accelerated computing. The Hopper GPU is paired with the Grace CPU using NVIDIA’s ultra-fast chip-to-chip interconnect, delivering 900GB/s of bandwidth, 7X faster than PCIe Gen5. This innovative design will deliver up to 30X higher aggregate system memory bandwidth to the GPU compared to today’s fastest servers and up to 10X higher performance for applications running terabytes of data.
Product Specifications
| Form Factor | H100 SXM | H100 PCIe | H100 NVL1 |
|---|---|---|---|
| FP64 | 34 teraFLOPS | 26 teraFLOPS | 68 teraFLOPs |
| FP64 Tensor Core | 67 teraFLOPS | 51 teraFLOPS | 134 teraFLOPs |
| FP32 | 67 teraFLOPS | 51 teraFLOPS | 134 teraFLOPs |
| TF32 Tensor Core | 989 teraFLOPS2 | 756 teraFLOPS2 | 1,979 teraFLOPs2 |
| BFLOAT16 Tensor Core | 1,979 teraFLOPS2 | 1,513 teraFLOPS2 | 3,958 teraFLOPs2 |
| FP16 Tensor Core | 1,979 teraFLOPS2 | 1,513 teraFLOPS2 | 3,958 teraFLOPs2 |
| FP8 Tensor Core | 3,958 teraFLOPS2 | 3,026 teraFLOPS2 | 7,916 teraFLOPs2 |
| INT8 Tensor Core | 3,958 TOPS2 | 3,026 TOPS2 | 7,916 TOPS2 |
| GPU memory | 80GB | 80GB | 188GB |
| GPU memory bandwidth | 3.35TB/s | 2TB/s | 7.8TB/s3 |
| Decoders | 7 NVDEC 7 JPEG | 7 NVDEC 7 JPEG | 14 NVDEC 14 JPEG |
| Max thermal design power (TDP) | Up to 700W (configurable) | 300-350W (configurable) | 2x 350-400W (configurable) |
| Multi-Instance GPUs | Up to 7 MIGS @ 10GB each | Up to 14 MIGS @ 12GB each | |
| Form factor | SXM | PCIe dual-slot air-cooled | 2x PCIe dual-slot air-cooled |
| Interconnect | NVLink: 900GB/s PCIe Gen5: 128GB/s | NVLink: 600GB/s PCIe Gen5: 128GB/s | NVLink: 600GB/s PCIe Gen5: 128GB/s |
| Server options | NVIDIA HGX H100 Partner and NVIDIA-Certified Systems™ with 4 or 8 GPUs NVIDIA DGX H100 with 8 GPUs | Partner and NVIDIA-Certified Systems with 1–8 GPUs | Partner and NVIDIA-Certified Systems with 2-4 pairs |
| NVIDIA AI Enterprise | Add-on | Included | Included |
1. Preliminary specifications. May be subject to change. Specifications shown for 2x H100 NVL PCIe cards paired with NVLink Bridge.
2. With sparsity.
3. Aggregate HBM bandwidth.
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