AMD Radeon Instinct MI250X
About GPU
The AMD Radeon Instinct MI250X GPU is a powerful and highly capable professional-grade graphics processing unit. With a base clock speed of 1000MHz and a boost clock speed of 1700MHz, this GPU offers impressive performance for a wide range of professional applications, including machine learning, AI, and data analytics.
One of the most noteworthy features of the AMD Radeon Instinct MI250X GPU is its substantial 128GB of high-bandwidth memory (HBM2e) and a memory clock speed of 1600MHz. This allows for the seamless processing of large datasets and complex computations, making it an ideal choice for professionals working with high-performance computing workloads.
The GPU also boasts an impressive 14080 shading units and 16MB of L2 cache, further contributing to its exceptional computational power. With a TDP of 500W, this GPU is designed to handle demanding workloads without compromising on performance.
In terms of theoretical performance, the AMD Radeon Instinct MI250X GPU delivers an outstanding 47.87 TFLOPS, making it one of the most powerful GPUs in its class. This level of performance ensures that professionals can tackle the most complex and data-intensive tasks with ease and efficiency.
Overall, the AMD Radeon Instinct MI250X GPU is a top-of-the-line graphics processing unit that offers exceptional performance, making it an excellent choice for professionals working in fields that require high-performance computing capabilities. Its impressive specifications and features make it well-suited for a wide range of professional applications, making it a valuable asset for those in need of high-performance computing power.
Basic
Label Name
AMD
Platform
Professional
Launch Date
November 2021
Model Name
Radeon Instinct MI250X
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.
1496 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.
383.0 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.
47.87 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.
48.827
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.
14080
L1 Cache
16 KB (per CU)
L2 Cache
16MB
TDP
500W
Benchmarks
FP32 (float)
Score
48.827
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS