Intel Data Center GPU Max 1350

Intel Data Center GPU Max 1350

About GPU

The Intel Data Center GPU Max 1350 is a professional-grade GPU that offers impressive performance for data center workloads. With a base clock of 750MHz and a boost clock of 1550MHz, this GPU is capable of handling demanding tasks with ease. The 96GB of HBM2e memory and a memory clock of 1200MHz ensure that it can efficiently handle large datasets and complex computations. One of the most impressive aspects of the Intel Data Center GPU Max 1350 is its 14336 shading units, which enable it to execute a high number of parallel tasks simultaneously. Additionally, the 408MB of L2 cache helps reduce latency and improve overall performance. With a TDP of 450W, this GPU is power-hungry but delivers exceptional performance in return. The theoretical performance of 44.44 TFLOPS further underscores its capabilities for handling intensive workloads. In a data center environment, the Intel Data Center GPU Max 1350 would excel at tasks such as AI training, high-performance computing, and data analytics. Its high memory capacity, impressive shading units, and overall performance make it a compelling choice for organizations looking to bolster their data center infrastructure. Overall, the Intel Data Center GPU Max 1350 is a powerhouse GPU that offers exceptional performance for professional applications. Its high memory capacity, impressive shading units, and overall performance make it a compelling choice for organizations looking to bolster their data center infrastructure.

Basic

Label Name
Intel
Platform
Professional
Launch Date
January 2023
Model Name
Data Center GPU Max 1350
Generation
Data Center GPU
Base Clock
750MHz
Boost Clock
1550MHz
Bus Interface
PCIe 5.0 x16
Transistors
100,000 million
RT Cores
112
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.
896
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.
896
Foundry
Intel
Process Size
10 nm
Architecture
Generation 12.5

Memory Specifications

Memory Size
96GB
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
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.
2458 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.
1389 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.
44.44 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.
44.44 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.
45.329 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.
14336
L1 Cache
64 KB (per EU)
L2 Cache
408MB
TDP
450W
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)
Shader Model
6.6
Suggested PSU
850W

Benchmarks

FP32 (float)
Score
45.329 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS
60.838 +34.2%
50.45 +11.3%
35.873 -20.9%