AMD Instinct MI100
The AMD Instinct MI100 GPU is a professional-grade graphics processing unit designed for high-performance computing and data-intensive workloads. With a base clock speed of 1000MHz and a boost clock of 1502MHz, this GPU offers exceptional processing power for a wide range of applications.
One of the most impressive features of the Instinct MI100 is its massive 32GB of HBM2 memory, which allows for handling large datasets and complex calculations with ease. The 1200MHz memory clock further enhances the data transfer speeds, ensuring smooth and efficient performance.
With 7680 shading units and 8MB of L2 cache, the MI100 GPU is capable of handling highly parallel workloads and complex computational tasks. This makes it an ideal choice for deep learning, scientific simulations, and other demanding applications.
Despite its powerful performance, the AMD Instinct MI100 GPU is also energy-efficient, with a TDP of 300W. This ensures that it can deliver high performance without consuming excessive amounts of power.
The theoretical performance of 23.07 TFLOPS demonstrates the immense computational power of this GPU, making it well-suited for mission-critical tasks that require rapid data processing and analysis.
Overall, the AMD Instinct MI100 GPU is a highly capable and versatile solution for professionals and organizations that require uncompromising performance for their data-driven workloads. Whether used for AI research, computational biology, or complex simulations, the MI100 GPU delivers exceptional performance and reliability.
Basic
Label Name
AMD
Platform
Professional
Launch Date
November 2020
Model Name
Radeon Instinct MI100
Generation
Radeon Instinct
Base Clock
1000MHz
Boost Clock
1502MHz
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
1200MHz
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.
1229 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.
96.13 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.
721.0 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.
184.6 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.
11.54 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.
22.609
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.
7680
L1 Cache
16 KB (per CU)
L2 Cache
8MB
TDP
300W
Benchmarks
FP32 (float)
Score
22.609
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS
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