AMD Instinct MI250
About GPU
The AMD Instinct MI250 is a professional-grade GPU designed for high-performance computing and artificial intelligence applications. With a base clock of 1000MHz and a boost clock of 1700MHz, the MI250 offers impressive processing power for demanding workloads.
One of the standout features of the MI250 is its large 128GB memory size, which is backed by HBM2e memory type and a memory clock of 1600MHz. This allows for fast and efficient data processing, making it suitable for intensive data analytics and machine learning tasks.
With an impressive 13312 shading units and 16MB of L2 cache, the MI250 is capable of handling complex computational tasks with ease. The TDP of 500W reflects the GPU's high power requirements, but the theoretical performance of 45.26 TFLOPS justifies the power consumption, making it suitable for performance-critical applications.
In real-world applications, the MI250 excels in tasks such as deep learning, scientific simulations, and data analytics, where its massive processing power and high memory capacity can be fully utilized.
Overall, the AMD Instinct MI250 is a formidable GPU for professionals and researchers who require cutting-edge performance for their compute-intensive workloads. While its power requirements may be a consideration for some users, the GPU's exceptional performance and features make it a compelling choice for those in need of top-tier computing power.
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.
44.355
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
44.355
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS