AMD Radeon Instinct MI60
About GPU
The AMD Radeon Instinct MI60 GPU is a powerful professional-grade GPU designed for demanding workloads such as deep learning, AI, and HPC (high-performance computing) applications. With a base clock of 1200MHz and a boost clock of 1800MHz, this GPU provides impressive performance for handling complex computational tasks.
One of the standout features of the AMD Radeon Instinct MI60 is its large 32GB HBM2 memory size, which allows for handling large datasets and complex models with ease. The high memory clock of 1000MHz ensures fast access to data, further boosting performance.
With 4096 shading units and 4MB of L2 cache, this GPU is capable of handling parallel processing tasks efficiently, making it well-suited for compute-intensive workloads. The TDP of 300W indicates that this GPU is power-hungry, but it is in line with other high-end professional GPUs.
The theoretical performance of 14.455 TFLOPS is impressive and highlights the GPU's ability to handle complex calculations and simulations.
Overall, the AMD Radeon Instinct MI60 GPU is a top-of-the-line solution for professionals and organizations that require high-performance computing capabilities. Its combination of high memory size, fast memory clock, and powerful shading units make it a formidable choice for AI, deep learning, and HPC workloads. Despite its high power requirements, the performance and capabilities of this GPU make it a worthwhile investment for those in need of top-tier compute power.
Basic
Label Name
AMD
Platform
Professional
Launch Date
November 2018
Model Name
Radeon Instinct MI60
Generation
Radeon Instinct
Base Clock
1200MHz
Boost Clock
1800MHz
Bus Interface
PCIe 4.0 x16
Memory Specifications
Memory Size
32GB
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.
4096bit
Memory Clock
1000MHz
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.
1024 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.
115.2 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.
460.8 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.
29.49 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.
7.373 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.
14.455
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
14.455
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS