AMD Radeon Instinct MI8
About GPU
The AMD Radeon Instinct MI8 GPU is a powerful and efficient professional-grade GPU that offers impressive performance for a wide range of compute-intensive tasks. With 4GB of HBM memory and a memory clock speed of 500MHz, this GPU is well-equipped to handle demanding workloads with ease.
One of the standout features of the Radeon Instinct MI8 is its impressive 8.028 TFLOPS of theoretical performance, making it an ideal choice for tasks such as machine learning, data analytics, and scientific computing. With 4096 shading units and 2MB of L2 cache, this GPU offers exceptional parallel processing power, allowing for fast and efficient computation.
In addition to its impressive performance capabilities, the Radeon Instinct MI8 is also relatively power-efficient, with a TDP of 175W. This makes it a great choice for organizations looking to maximize their compute performance while minimizing their energy consumption.
Overall, the AMD Radeon Instinct MI8 GPU is a standout choice for professional applications that require high-performance computing. Its combination of powerful hardware specs and power efficiency make it a compelling option for organizations looking to accelerate their workloads and drive innovation in their respective fields. Whether you're working in machine learning, data analytics, or scientific computing, the Radeon Instinct MI8 is a GPU that is worth considering for your next project.
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.
8.028
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
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.
1.2.170
OpenCL Version
2.1
Benchmarks
FP32 (float)
Score
8.028
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS