AMD Instinct MI300A
About GPU
The AMD Instinct MI300A is a powerhouse GPU designed for professional use, particularly in data centers and scientific applications. With a base clock of 1000MHz and a boost clock of 2100MHz, the MI300A offers impressive speed and performance for demanding workloads.
One of the most remarkable features of the MI300A is its massive memory size of 128GB, combined with high-bandwidth HBM3 memory type and a clock speed of 5200MHz. This configuration enables the GPU to handle large datasets and complex calculations with ease, making it an ideal choice for AI, machine learning, and HPC workloads.
The MI300A boasts a staggering 14592 shading units, ensuring smooth and efficient parallel processing. Additionally, with 16MB of L2 cache, the GPU can minimize data access latency, further optimizing its performance.
As a professional-grade GPU, the MI300A has a TDP of 760W, which may require robust cooling and power delivery systems in a data center environment. However, this level of power consumption is justified by the GPU's theoretical performance of 122.6 TFLOPS, making it one of the most powerful options available for professional applications.
Overall, the AMD Instinct MI300A GPU is a game-changer for data centers and scientific computing, offering unparalleled performance, massive memory capacity, and advanced features that cater to the most demanding workloads. Its impressive specs make it a compelling choice for professionals who require top-tier performance for their applications.
Basic
Label Name
AMD
Platform
Professional
Launch Date
December 2023
Model Name
Instinct MI300A
Generation
Instinct
Base Clock
1000MHz
Boost Clock
2100MHz
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
5200MHz
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.
5300 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.
980.6 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.
61.3 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.
120.148
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.
14592
L1 Cache
16 KB (per CU)
L2 Cache
16MB
TDP
760W
Benchmarks
FP32 (float)
Score
120.148
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS