AMD Radeon Instinct MI250
About GPU
The AMD Radeon Instinct MI250 GPU is a professional-grade graphics card designed for high-performance computing and data processing tasks. With a base clock speed of 1000MHz and a boost clock speed of 1700MHz, this GPU is capable of delivering exceptional performance for a wide range of applications.
One of the standout features of the Radeon Instinct MI250 is its massive 128GB of HBM2e memory, which sets it apart from many other GPUs on the market. This large memory size, combined with a memory clock speed of 1600MHz, allows the MI250 to handle large datasets and complex calculations with ease.
With 13312 shading units and 16MB of L2 cache, the Radeon Instinct MI250 is capable of handling demanding workloads and delivering fast and efficient performance. The GPU also has a TDP of 500W, which may be on the higher end, but it is justified given its impressive theoretical performance of 45.26 TFLOPS.
Overall, the AMD Radeon Instinct MI250 GPU is a powerhouse when it comes to professional use cases. From scientific research to machine learning and artificial intelligence, this GPU has the capability to handle the most complex and data-intensive tasks. While it may not be a practical choice for casual gaming or everyday use, the MI250 excels in the realm of high-performance computing and is a top choice for professionals in need of exceptional GPU capabilities.
Basic
Label Name
AMD
Platform
Professional
Launch Date
November 2021
Model Name
Radeon Instinct MI250
Generation
Radeon Instinct
Base Clock
1000MHz
Boost Clock
1700MHz
Bus Interface
PCIe 4.0 x16
Memory Specifications
Memory Size
128GB
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.
8192bit
Memory Clock
1600MHz
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.
3277 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.
0 MPixel/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.
1414 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.
362.1 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.
45.26 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.
46.165
TFLOPS
Miscellaneous
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.
13312
L1 Cache
16 KB (per CU)
L2 Cache
16MB
TDP
500W
Benchmarks
FP32 (float)
Score
46.165
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS