AMD Radeon Instinct MI300
About GPU
The AMD Radeon Instinct MI300 GPU is a powerful professional-grade GPU designed for data center and HPC workloads. With a base clock speed of 1000MHz and a boost clock speed of 1700MHz, this GPU offers impressive performance for a wide range of compute-intensive tasks.
One of the standout features of the Radeon Instinct MI300 is its massive 128GB of HBM3 memory, which allows for large datasets to be processed quickly and efficiently. The memory clock speed of 1600MHz ensures that data can be accessed and manipulated at a rapid pace, further enhancing overall performance.
The GPU also boasts an impressive 14080 shading units, as well as 16MB of L2 cache, allowing for complex calculations and simulations to be handled with ease. The high TDP of 600W ensures that the GPU can consistently deliver high levels of performance without throttling, making it well-suited for demanding workloads.
The theoretical performance of 47.87 TFLOPS demonstrates the sheer computational power of this GPU, making it an ideal choice for tasks such as machine learning, data analytics, and scientific simulations.
Overall, the AMD Radeon Instinct MI300 GPU is a top-of-the-line choice for professionals and organizations seeking a high-performance computing solution. Its impressive specs and high level of computational power make it well-equipped to handle the most demanding workloads with ease.
Basic
Label Name
AMD
Platform
Professional
Launch Date
January 2023
Model Name
Radeon Instinct MI300
Generation
Radeon Instinct
Base Clock
1000MHz
Boost Clock
1700MHz
Bus Interface
PCIe 5.0 x16
Memory Specifications
Memory Size
128GB
Memory Type
HBM3
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.
8192bit
Memory Clock
1600MHz
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.
3277 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.
0 MPixel/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.
1496 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.
383.0 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.
47.87 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.
46.913
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.
14080
L1 Cache
16 KB (per CU)
L2 Cache
16MB
TDP
600W
Benchmarks
FP32 (float)
Score
46.913
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS