AMD Radeon Instinct MI25
About GPU
The AMD Radeon Instinct MI25 GPU is a professional-grade graphics processing unit designed for high-performance computing and artificial intelligence workloads. With a base clock of 1400MHz and a boost clock of 1500MHz, this GPU offers powerful processing capabilities to handle complex tasks with ease.
One of the standout features of the Radeon Instinct MI25 is its 16GB of HBM2 memory, which provides high bandwidth and low latency for handling large datasets and memory-intensive applications. The 852MHz memory clock further enhances the GPU's ability to handle data-intensive workloads with speed and efficiency.
With 4096 shading units and 4MB of L2 cache, the Radeon Instinct MI25 offers impressive parallel processing capabilities, making it well-suited for deep learning, data analytics, and other compute-intensive tasks. The GPU's 300W TDP ensures that it can deliver high levels of performance without compromising on power efficiency.
In terms of performance, the Radeon Instinct MI25 boasts a theoretical performance of 12.536 TFLOPS, making it a formidable choice for demanding professional workloads. Whether it's training neural networks, running simulations, or conducting data analysis, this GPU is well-equipped to handle the most challenging tasks.
Overall, the AMD Radeon Instinct MI25 GPU is a compelling option for professionals and organizations seeking a high-performance computing solution for AI, machine learning, and HPC applications. Its impressive specifications and strong performance make it a valuable asset for accelerating complex workloads and driving innovation in various industries.
Basic
Label Name
AMD
Platform
Professional
Launch Date
June 2017
Model Name
Radeon Instinct MI25
Generation
Radeon Instinct
Base Clock
1400MHz
Boost Clock
1500MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
16GB
Memory Type
HBM2
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.
2048bit
Memory Clock
852MHz
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.
436.2 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.
96.00 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.
384.0 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.
24.58 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.
768.0 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.
12.536
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.
4096
L1 Cache
16 KB (per CU)
L2 Cache
4MB
TDP
300W
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.
1.2
OpenCL Version
2.1
Benchmarks
FP32 (float)
Score
12.536
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS