NVIDIA H100 SXM5 64 GB
About GPU
The NVIDIA H100 SXM5 64GB GPU is a professional-grade graphics processing unit that boasts impressive specs and delivers top-notch performance. With a base clock of 1665MHz and a boost clock of 1980MHz, this GPU offers high-speed performance for demanding tasks such as AI, deep learning, and scientific computing.
One of the standout features of the H100 is its massive 64GB of HBM3 memory, which allows for seamless handling of large datasets and complex calculations. The memory clock speed of 1313MHz further enhances the overall performance of the GPU, making it a suitable choice for data-intensive workloads.
With an impressive 16896 shading units and 50MB of L2 cache, the H100 is designed to handle complex and computationally intensive tasks with ease. The TDP of 700W showcases the power and efficiency of this GPU, ensuring that it can deliver reliable performance without compromising on energy consumption.
Theoretical performance metrics indicate that the H100 is capable of delivering an impressive 66.91 TFLOPS, making it a powerhouse for parallel processing and high-performance computing tasks.
Overall, the NVIDIA H100 SXM5 64GB GPU is a high-performance solution for professionals and organizations that require top-tier capabilities for AI, deep learning, and scientific computing. Its robust specs, large memory capacity, and efficient design make it a compelling choice for those seeking cutting-edge GPU technology.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
March 2022
Model Name
H100 SXM5 64 GB
Generation
Tesla Hopper
Base Clock
1665MHz
Boost Clock
1980MHz
Bus Interface
PCIe 5.0 x16
Memory Specifications
Memory Size
64GB
Memory Type
HBM3
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
3072bit
Memory Clock
1313MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
3350 GB/s
Theoretical Performance
Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
47.52 GPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
1045 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
267.6 TFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
33.45 TFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
68.248
TFLOPS
Miscellaneous
SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
132
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
16896
L1 Cache
256 KB (per SM)
L2 Cache
50MB
TDP
700W
Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
N/A
OpenCL Version
3.0
Benchmarks
FP32 (float)
Score
68.248
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS