NVIDIA A10M
About GPU
The NVIDIA A10M GPU is a powerhouse in the professional platform, offering exceptional performance and capabilities for a variety of professional applications. With a base clock of 975MHz and a boost clock of 1635MHz, this GPU delivers impressive speeds and capabilities for demanding workloads.
One of the standout features of the A10M is its massive 24GB of GDDR6 memory, which allows for handling large datasets and complex simulations with ease. The memory clock of 1563MHz ensures fast and efficient data processing, while the 6MB L2 cache helps to reduce latency and improve overall performance.
With 7168 shading units, the A10M is capable of handling complex rendering and visualization tasks with ease. Its 150W TDP ensures that it can deliver high levels of performance without overheating or wasting energy.
The theoretical performance of 22.971 TFLOPS makes the A10M an ideal choice for professionals working in fields such as data science, engineering, and content creation. Whether you're working with large-scale simulations, rendering high-resolution graphics, or processing massive datasets, the A10M has the capabilities to handle it all.
Overall, the NVIDIA A10M GPU is a top-of-the-line option for professionals who require high levels of performance, reliability, and scalability. Its impressive specifications and capabilities make it a standout choice for a wide range of professional applications, and its robust design ensures that it can handle even the most demanding workloads with ease.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
February 2022
Model Name
A10M
Generation
Tesla Ampere
Base Clock
975MHz
Boost Clock
1635MHz
Bus Interface
PCIe 4.0 x16
Memory Specifications
Memory Size
24GB
Memory Type
GDDR6
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.
384bit
Memory Clock
1563MHz
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.
600.2 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.
130.8 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.
366.2 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.
23.44 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.
732.5 GFLOPS
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.
22.971
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.
56
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.
7168
L1 Cache
128 KB (per SM)
L2 Cache
6MB
TDP
150W
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.
1.3
OpenCL Version
3.0
Benchmarks
FP32 (float)
Score
22.971
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS