NVIDIA A100 PCIe
About GPU
The NVIDIA A100 PCIe GPU is a powerhouse for professional computing tasks. With a base clock of 765MHz and a boost clock of 1410MHz, this GPU delivers high performance for a wide range of applications. Its massive 40GB of HBM2e memory and a memory clock of 1215MHz ensure that it can handle large datasets and memory-intensive workloads with ease.
With an impressive 6912 shading units and 40MB of L2 cache, the A100 PCIe GPU is built to handle complex computations and demanding graphics workloads. Its TDP of 250W may be higher than some other GPUs, but the level of performance it delivers makes it worth the power consumption.
One of the most remarkable features of the A100 PCIe GPU is its theoretical performance of 19.49 TFLOPS, making it a top choice for AI, deep learning, and data analytics tasks. Its high performance and robust feature set make it an ideal option for professionals in fields such as scientific research, engineering, and content creation.
Overall, the NVIDIA A100 PCIe GPU is a top-of-the-line professional GPU that offers exceptional performance and capabilities. Its high memory capacity, powerful shading units, and impressive theoretical performance make it a standout choice for professionals seeking a GPU that can handle the most demanding computing workloads. While it may come with a higher power consumption, its performance and features make it well worth the investment.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
June 2020
Model Name
A100 PCIe
Generation
Tesla
Base Clock
765MHz
Boost Clock
1410MHz
Bus Interface
PCIe 4.0 x16
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.
19.1
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
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
19.1
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS