AMD Radeon Instinct MI325X
The AMD Radeon Instinct MI325X GPU is a powerhouse designed for high-performance computing in the desktop platform. With a base clock of 1000 MHz and a boost clock of 2100 MHz, this GPU delivers exceptional speed and efficiency for demanding workloads.
One of the most impressive features of the MI325X is its massive 288GB of HBM3e memory, coupled with a memory clock of 2525 MHz. This allows the GPU to handle large datasets and complex calculations with ease, making it an ideal choice for data analytics, machine learning, and other compute-intensive tasks.
The GPU is equipped with 19456 shading units, providing the necessary parallel processing power for accelerated computing. Additionally, it boasts a sizable 16 MB L2 cache, further enhancing its ability to handle massive amounts of data.
With a TDP of 750W, the MI325X is a high-power GPU designed for professional applications that require uncompromising performance. Its theoretical performance of 83.354 TFLOPS ensures that it can handle the most demanding workloads with ease, making it a compelling choice for professionals who require top-tier compute performance.
Overall, the AMD Radeon Instinct MI325X GPU is a formidable solution for high-performance computing needs. Its combination of high memory capacity, fast memory speeds, and massive parallel processing power make it a compelling choice for professionals in need of uncompromising compute performance.
Basic
Label Name
AMD
Platform
Desktop
Launch Date
October 2024
Model Name
Radeon Instinct MI325X
Generation
Radeon Instinct
Base Clock
1000 MHz
Boost Clock
2100 MHz
Bus Interface
PCIe 5.0 x16
Transistors
153 billion
Compute Units
304
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
1216
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
1216
Foundry
TSMC
Process Size
5 nm
Architecture
CDNA 3.0
Memory Specifications
Memory Size
288GB
Memory Type
HBM3e
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
2525 MHz
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.
10.3TB/s
Theoretical Performance
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.
2554 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.
653.7 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.
81.72 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.
83.354
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.
19456
L1 Cache
16 KB (per CU)
L2 Cache
16 MB
TDP
750W
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.
N/A
OpenCL Version
3.0
OpenGL
N/A
DirectX
N/A
Power Connectors
None
Shader Model
N/A
Suggested PSU
1150 W
Benchmarks
FP32 (float)
Score
83.354
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS
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