NVIDIA H800 SXM5
About GPU
The NVIDIA H800 SXM5 GPU is a powerhouse of a professional graphics processing unit, boasting impressive specs and performance capabilities. With a base clock of 1095MHz and a boost clock of 1755MHz, this GPU delivers exceptional speed and responsiveness for demanding workloads.
One of the standout features of the H800 SXM5 is its massive 80GB of HBM3 memory, allowing for the handling of large datasets and complex simulations with ease. The high memory clock of 1313MHz further enhances the GPU's ability to process data efficiently.
Equipped with 16896 shading units and 50MB of L2 cache, the H800 SXM5 is optimized for parallel processing, making it well-suited for AI, deep learning, and scientific computing applications. This GPU's theoretical performance of 59.3 TFLOPS further underscores its ability to handle intensive computing tasks.
While the H800 SXM5's TDP of 700W may be on the higher end, it is a necessary tradeoff for the immense power and performance it delivers. It is important to ensure proper cooling and power supply when using this GPU in a workstation.
Overall, the NVIDIA H800 SXM5 GPU is an outstanding choice for professionals and organizations in need of top-tier performance for data-intensive workloads. Its impressive specifications and capabilities make it a valuable asset for AI research, scientific simulations, and other high-performance computing tasks.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
March 2022
Model Name
H800 SXM5
Generation
NVIDIA Hopper
Base Clock
1095MHz
Boost Clock
1755MHz
Bus Interface
PCIe 5.0 x16
Memory Specifications
Memory Size
80GB
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.
5120bit
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.
42.12 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.
926.6 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.
1979 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.
1 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.
60.486
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
60.486
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS