AMD Instinct MI8
About GPU
The AMD Instinct MI8 GPU is a top-of-the-line professional-grade graphics processing unit designed for demanding computing tasks. With a memory size of 4GB and memory type of HBM (High Bandwidth Memory), this GPU is optimized for high-performance computing and data-intensive tasks.
The AMD Instinct MI8 GPU features a memory clock of 500MHz, 4096 shading units, and 2MB of L2 cache, delivering a theoretical performance of 8.192 TFLOPS. This level of performance makes it suitable for a wide range of professional applications, including machine learning, artificial intelligence, and scientific simulations.
One of the key features of the AMD Instinct MI8 GPU is its power efficiency, with a TDP (thermal design power) rating of 175W. This makes it suitable for deployment in data centers and other environments where energy efficiency is a priority.
In real-world scenarios, the AMD Instinct MI8 GPU delivers exceptional performance, allowing for faster data processing and improved productivity. Its advanced features and high level of performance make it a valuable asset for professionals working in industries that require intensive computing power.
Overall, the AMD Instinct MI8 GPU is a highly capable and efficient graphics processing unit that is well-suited for professional applications. Its combination of high performance, power efficiency, and advanced features make it a compelling choice for professionals who need a GPU that can deliver reliable and consistent performance for their most demanding computing workloads.
Basic
Label Name
AMD
Platform
Professional
Launch Date
December 2016
Model Name
Radeon Instinct MI8
Generation
Radeon Instinct
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
4GB
Memory Type
HBM
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.
4096bit
Memory Clock
500MHz
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.
512.0 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.
64.00 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.
256.0 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.
8.192 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.
512.0 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.
8.356
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
2MB
TDP
175W
Benchmarks
FP32 (float)
Score
8.356
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS