NVIDIA H100 PCIe

NVIDIA H100 PCIe

About GPU

The NVIDIA H100 PCIe GPU is a powerhouse professional graphics card that offers an impressive set of specifications. With a base clock of 1095MHz and a boost clock of 1755MHz, this GPU delivers exceptional performance for demanding professional workloads. The 80GB of HBM2e memory and a memory clock of 1593MHz ensure that even the most memory-intensive tasks can be handled with ease. The 14592 shading units and 50MB of L2 cache make this GPU well-equipped for handling complex rendering and simulation tasks. One of the standout features of the NVIDIA H100 PCIe GPU is its impressive theoretical performance of 51.22 TFLOPS, which showcases its ability to handle high-performance computing workloads. This makes it an excellent choice for professionals working in fields such as data science, engineering, and content creation. In terms of power consumption, the H100 PCIe GPU has a TDP of 350W, which is on the higher end, but the performance it offers justifies the power usage. Additionally, this GPU is designed for use in professional workstations with adequate cooling and power supply capabilities. Overall, the NVIDIA H100 PCIe GPU is a top-of-the-line option for professionals who require a high-performance graphics solution. Its impressive specifications, including its large memory capacity, high core count, and exceptional theoretical performance, make it well-suited for intensive professional workloads. Whether you are working on complex simulations, rendering large datasets, or tackling other demanding tasks, the NVIDIA H100 PCIe GPU is a reliable and powerful choice.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
March 2022
Model Name
H100 PCIe
Generation
Tesla Hopper
Base Clock
1095MHz
Boost Clock
1755MHz
Bus Interface
PCIe 5.0 x16

Memory Specifications

Memory Size
80GB
Memory Type
HBM2e
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
1593MHz
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.
2039 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.
800.3 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.
204.9 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.
25.61 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.
52.244 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.
114
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.
14592
L1 Cache
256 KB (per SM)
L2 Cache
50MB
TDP
350W
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
52.244 TFLOPS
Blender
Score
5111
OpenCL
Score
267514

Compared to Other GPU

FP32 (float) / TFLOPS
52.763 +1%
52.326 +0.2%
52.244
52.244 -0%
Blender
5217 +2.1%
5111
5010 -2%
OpenCL
L40
292357 +9.3%
267514