NVIDIA H200 NVL
About GPU
The NVIDIA H200 NVL GPU is a powerhouse designed for high-performance computing and advanced AI applications, making it an essential asset for professionals in data science, deep learning, and complex simulations. With a robust base clock of 1365 MHz and a boost clock reaching 1785 MHz, users can expect impressive performance across a range of demanding tasks.
One of the standout features of the H200 NVL is its colossal 141GB HBM3e memory, which allows for massive datasets to be processed with exceptional speed and efficiency. The memory clock of 1313 MHz ensures that data transfer rates are optimal, providing a seamless experience even in memory-intensive applications. Coupled with 16896 shading units and a generous 50 MB L2 cache, this GPU is well-equipped to handle complex computations and high-resolution graphics.
Delivering a theoretical performance of 59.114 TFLOPS, the H200 NVL excels in tasks like real-time ray tracing and large-scale machine learning model training, redefining performance benchmarks in its class. While the 600W TDP might necessitate adequate cooling solutions, the trade-off is justified by the unparalleled computational capabilities it offers.
In conclusion, the NVIDIA H200 NVL GPU stands as a top choice for professionals seeking unrivaled performance and cutting-edge technology, reinforcing NVIDIA's dominance in the GPU market for compute-intensive applications. Whether for enterprise-level projects or ambitious research initiatives, this GPU is engineered to handle it all.
Basic
Label Name
NVIDIA
Platform
Desktop
Launch Date
November 2024
Model Name
H200 NVL
Generation
Tesla Hopper(Hxx)
Base Clock
1365 MHz
Boost Clock
1785 MHz
Bus Interface
PCIe 5.0 x16
Transistors
80 billion
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
528
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
528
Foundry
TSMC
Process Size
5 nm
Architecture
Hopper
Memory Specifications
Memory Size
141GB
Memory Type
HBM3e
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
1313 MHz
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.
3.36TB/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.
42.84 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.
942.5 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.
241.3 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.
30.16 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.
59.114
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
50 MB
TDP
600W
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
OpenGL
N/A
DirectX
N/A
CUDA
9.0
Power Connectors
8-pin EPS
Shader Model
N/A
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
24
Suggested PSU
1000 W
Benchmarks
FP32 (float)
Score
59.114
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS