Intel Data Center GPU Max Subsystem
The Intel Data Center GPU Max Subsystem GPU is a high-performance, professional-grade graphic processing unit designed for data center applications. With a base clock speed of 900MHz and boost clock speed of 1600MHz, this GPU offers impressive processing power for demanding workloads.
One of the standout features of this GPU is its massive 128GB HBM2e memory size, providing ample capacity for handling large datasets and complex calculations. Coupled with a memory clock speed of 1565MHz, the GPU can efficiently handle memory-intensive tasks without sacrificing performance.
With a staggering 16384 shading units and 408MB of L2 cache, the GPU offers exceptional parallel processing capabilities, making it well-suited for machine learning, data analytics, and other AI-driven workloads. The TDP of 2400W indicates that this GPU is a power-hungry component, so proper cooling and power delivery are essential for optimal performance.
The theoretical performance of 52.43 TFLOPS demonstrates the immense computing power of this GPU, making it an attractive option for data center environments where high-performance computing is a priority.
Overall, the Intel Data Center GPU Max Subsystem GPU is a compelling choice for data center deployments that require robust, scalable, and high-performance graphics processing capabilities. Its impressive specifications and features make it well-equipped to handle the demands of modern data center workloads, and it is sure to be a valuable asset for organizations focused on advanced computing tasks.
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Basic
Label Name
Intel
Platform
Professional
Launch Date
January 2023
Model Name
Data Center GPU Max Subsystem
Generation
Data Center GPU
Base Clock
900MHz
Boost Clock
1600MHz
Bus Interface
PCIe 5.0 x16
Transistors
100,000 million
RT Cores
128
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.
1024
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.
1024
Foundry
Intel
Process Size
10 nm
Architecture
Generation 12.5
Memory Specifications
Memory Size
128GB
Memory Type
HBM2e
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
1565MHz
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.
3205 GB/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.
1638 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.
52.43 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.
52.43 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.
51.381
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.
16384
L1 Cache
64 KB (per EU)
L2 Cache
408MB
TDP
2400W
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
4.6
DirectX
12 (12_1)
Power Connectors
1x 16-pin
Shader Model
6.6
Suggested PSU
2800W
Benchmarks
FP32 (float)
Score
51.381
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS