NVIDIA A100 SXM4 40 GB

NVIDIA A100 SXM4 40 GB

NVIDIA A100 SXM4 40 GB is a Professional video accelerator from NVIDIA. It began to be released in May 2020. The GPU has a boost frequency of 1410MHz. It also has a memory frequency of 1215MHz. Its characteristics, as well as benchmark results, are presented in more detail below.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
May 2020
Model Name
A100 SXM4 40 GB
Generation
Tesla
Base Clock
1095MHz
Boost Clock
1410MHz
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
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
Transistors
54,200 million
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.
432
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.
432
L1 Cache
192 KB (per SM)
L2 Cache
40MB
Bus Interface
PCIe 4.0 x16
Foundry
TSMC
Process Size
7 nm
Architecture
Ampere
TDP
400W

Memory Specifications

Memory Size
40GB
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
1215MHz
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.
1555 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.
19.484 TFlops

Miscellaneous

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
8.0
Power Connectors
None
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.
160
Shader Model
N/A
Suggested PSU
800W

FP32 (float)

19.484 TFlops

Blender

2275

OctaneBench

505

Compared to Other GPU

SiliconCat Rating

140
Ranks 140 among all GPU on our website
FP32 (float)
CMP 90HX
NVIDIA, July 2021
21.884 TFlops
Radeon RX 7700S
AMD, January 2023
20.888 TFlops
A100 SXM4 40 GB
NVIDIA, May 2020
19.484 TFlops
GeForce RTX 3080 Ti Mobile
NVIDIA, January 2022
18.704 TFlops
RTX A5000 Max-Q
NVIDIA, April 2021
16.92 TFlops
Blender
GeForce RTX 4090
NVIDIA, September 2022
12577
2912
A100 SXM4 40 GB
NVIDIA, May 2020
2275
Tesla M40 24 GB
NVIDIA, November 2015
589
Tesla K80
NVIDIA, November 2014
258
OctaneBench
GeForce RTX 4090
NVIDIA, September 2022
1341
A100 SXM4 40 GB
NVIDIA, May 2020
505
Tesla P40
NVIDIA, September 2016
167
GeForce GTX 780
NVIDIA, May 2013
88
T550 Mobile
NVIDIA, May 2022
47