NVIDIA GPU Graphics card family
NVIDIA GH100-885K-A1
- Product description: NVIDIA GH100-885K-A1_4nm Data Center Chip, up to 4000 Tflops Compute, Hbm3 3 Tb/S Memory_liyuan tech
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Brand: NVIDIA
Part Number: GH100-885K-A1
Product Description
NVIDIA H100 is a flagship-level data center GPU specifically designed to accelerate artificial intelligence, data analysis, and high-performance computing.
It represents another significant leap in NVIDIA's GPU technology compared to its predecessor, the A100. It has achieved remarkable improvements in both performance and functionality.
4nm Process: Manufactured using TSMC's 4N process, it integrates up to 80 billion transistors. The more advanced process brings higher energy efficiency and performance density.
up to 4000 Tflops Compute (up to 4000 trillion floating-point operations per second): This is a crucial figure, referring to the tensor operation performance at FP8 precision.
This is a performance metric specifically optimized for AI training and inference, demonstrating its terrifying computing power when handling large-scale AI models (such as the large language model GPT-4, etc.).
Its FP64 (double precision, used for traditional scientific computing) performance is approximately 60 Tflops, and the FP16/FP32 performance is also extremely strong.
HBM3 3 Tb/S Memory (HBM3 memory, with a bandwidth of up to 3TB/second): HBM3 is the current most advanced high-bandwidth memory technology.
The up to 3TB/s bandwidth means that data can be transmitted at an extremely fast speed between GPU cores and memory,
which is crucial for processing AI models with massive parameters and scientific computations requiring huge datasets,
effectively avoiding the "memory wall" bottleneck. The H100 can be equipped with up to 80GB of HBM3 memory.
Other core features:
Revolutionary Transformer Engine: Specifically designed to accelerate the Transformer architecture (the foundation of all current large language models),
able to dynamically and intelligently handle FP8 and FP16 precisions, without sacrificing precision, and significantly increasing the training and inference speed of such models by several times.
Second-generation MIG (Multi-Instance GPU) Technology: Can divide a physical H100 GPU into up to 7 independent,
secure small GPU instances, allowing different users or tasks to share the same GPU, greatly improving the utilization and flexibility of the data center.
Fourth-generation NVLink: Interconnection bandwidth up to 900GB/s (7 times that of PCIe 5.0),
allowing multiple H100 GPUs to be seamlessly connected, working like a giant unified GPU, which is crucial for expanding large-scale AI training and supercomputing clusters.
DPX Instructions: A new set of instruction sets that can significantly accelerate dynamic programming algorithms, bringing orders of magnitude in performance improvement in fields such as healthcare, robotics, and path optimization.
Confidential Computing: Capable of encrypting the data being processed on the GPU, protecting the security of customer sensitive data and AI models,
which is very important for cloud service providers and strictly regulated industries. Usage scenario
The NVIDIA H100 is essentially designed for the most demanding computing tasks. Its main application scenarios include:
1. AI training and large language models (LLMs)
Scenario: Training ultra-large-scale foundational models with trillions or even quadrillions of parameters, such as GPT-4, PaLM, and Claude.
Why H100: Its Transformer engine and FP8 ultra-high performance are specifically optimized for such workloads, reducing training time from months to weeks or even days.
2. AI inference and deployment
Scenario: Deploying and running already trained large AI models in the cloud (such as ChatGPT, Midjourney, etc.) or on an enterprise's internal network to provide real-time responses to millions of users.
Why H100: Its extremely high throughput and energy efficiency enable it to handle more user requests at the same power consumption, significantly reducing the operational costs of large-scale AI services.
3. High-performance computing (HPC) and digital twins
Scenario: Climate prediction, astrophysical simulation, new drug development, genetic sequencing, fluid dynamics calculation, creating "digital twin" models of entire cities or factories.
Why H100: Its powerful FP64 double-precision computing capability and high-speed NVLink interconnection allow researchers to solve complex scientific and engineering problems that were previously unsolvable.
4. Data analysis and recommendation systems
Scenario: Processing massive user data for companies like Netflix, Amazon, and TikTok, running complex recommendation algorithms.
Why H100: Its huge memory bandwidth and computing power can quickly process TB-level data sets, providing users with real-time, precise personalized recommendations.
5. Genomics and medical health
Scenario: Accelerating genome sequence alignment, protein structure prediction (such as AlphaFold), medical image analysis, and new drug molecule simulation.
In addition to NVIDIA GH100-885K-A1 , Liyuan Tech supply a wide range of other NVIDIA GPU Graphics card family . If you have any need or interest, please feel free to send inquiry to global@chn-liyuan.com
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