NVIDIA A100 SXM4 80 GB
About GPU
The NVIDIA A100 SXM4 80 GB GPU is a powerhouse of a graphics processing unit, designed for professional use in data centers and supercomputing environments. With a base clock speed of 1275MHz and a boost clock speed of 1410MHz, this GPU offers impressive performance for a wide range of demanding workloads.
One of the standout features of the A100 SXM4 is its massive 80GB of HBM2e memory, which is incredibly beneficial for handling large-scale data processing and machine learning tasks. The high memory clock speed of 1593MHz ensures that data can be accessed and processed quickly, contributing to overall efficiency and productivity.
With 6912 shading units and 40MB of L2 cache, the A100 SXM4 is capable of handling complex and computationally intensive workloads with ease. Its 400W TDP may be higher than some other GPUs, but it is a necessary trade-off for the level of performance and capabilities that it offers.
The theoretical performance of 19.49 TFLOPS further illustrates the A100 SXM4's potential for tackling demanding computational tasks, making it an ideal choice for AI training, inference, and other deep learning applications.
Overall, the NVIDIA A100 SXM4 80 GB GPU is a top-of-the-line solution for professionals and organizations that require high-performance computing capabilities. Its impressive specifications and capabilities make it well-suited for a variety of advanced workloads, and it is a valuable addition to any data center or supercomputing environment.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
November 2020
Model Name
A100 SXM4 80 GB
Generation
Ampere
Base Clock
1275MHz
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.
19.1
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
40MB
TDP
400W
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
19.1
TFLOPS
OctaneBench
Score
526
Compared to Other GPU
FP32 (float)
/ TFLOPS
OctaneBench