AMD Instinct MI60

AMD Instinct MI60

About GPU

The AMD Instinct MI60 GPU is a powerful and efficient professional-grade graphics card that is designed for high-performance computing and machine learning tasks. With a base clock of 1200MHz and a boost clock of 1800MHz, this GPU is capable of delivering exceptional processing power for a wide range of applications. One of the standout features of the Instinct MI60 is its impressive 32GB of HBM2 memory, which provides ample capacity for handling large datasets and complex computational workloads. Additionally, the memory clock speed of 1000MHz ensures speedy access to data, further enhancing the GPU's overall performance. With 4096 shading units and 4MB of L2 cache, the Instinct MI60 is well-equipped to handle demanding parallel processing tasks with ease. Its TDP of 300W, while relatively high, is a reasonable trade-off for the immense computational power it offers. Furthermore, the GPU's theoretical performance of 14.75 TFLOPS underscores its ability to tackle intensive workloads effectively. Overall, the AMD Instinct MI60 GPU is a top-tier solution for professionals in fields such as scientific research, data analytics, and artificial intelligence. Its combination of high memory capacity, fast clock speeds, and substantial computational performance make it an excellent choice for demanding workloads. Whether you're training complex machine learning models or conducting intricate simulations, the Instinct MI60 is more than capable of meeting your needs.

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.
15.045 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

Benchmarks

FP32 (float)
Score
15.045 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS
16.023 +6.5%
15.709 +4.4%
15.045
14.413 -4.2%
13.808 -8.2%