NVIDIA A800 PCIe 80 GB
About GPU
The NVIDIA A800 PCIe 80GB GPU is a powerful and high-performance graphics processing unit designed for professional use. With a base clock of 1065MHz and a boost clock of 1410MHz, this GPU offers incredible speed and efficiency for a wide range of professional applications.
One of the standout features of the A800 PCIe 80GB GPU is its massive 80GB memory size, utilizing HBM2e memory type and operating at a clock speed of 1593MHz. This large memory capacity allows for the handling of massive datasets and complex computational tasks with ease, making it well-suited for data science, deep learning, and other demanding workloads.
The GPU boasts a staggering 6912 shading units and an impressive 80MB L2 cache, resulting in seamless and responsive performance for even the most demanding tasks. The TDP of 250W ensures efficient power usage while delivering exceptional computational power.
With a theoretical performance of 19.49 TFLOPS, the NVIDIA A800 PCIe 80GB GPU is capable of handling the most demanding workloads with ease, making it an ideal choice for professionals in fields such as scientific research, artificial intelligence, and high-performance computing.
Overall, the NVIDIA A800 PCIe 80GB GPU offers exceptional performance, advanced features, and impressive specifications, making it a top choice for professionals seeking a high-performance GPU for their professional workloads.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
November 2022
Model Name
A800 PCIe 80 GB
Generation
Ampere
Base Clock
1065MHz
Boost Clock
1410MHz
Bus Interface
PCIe 4.0 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.
225.6 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.
609.1 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.
77.97 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.
9.746 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.
19.88
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.
108
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.
6912
L1 Cache
192 KB (per SM)
L2 Cache
80MB
TDP
250W
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
19.88
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS