Intel Data Center GPU Max 1100
The Intel Data Center GPU Max 1100 is an impressive addition to the lineup of data center GPUs. With a professional-grade platform and robust specs, this GPU is designed to handle the most demanding workloads and applications.
One of the standout features of the Max 1100 is its massive 48GB of HBM2e memory, providing ample space for large datasets and memory-intensive tasks. The high memory clock speed of 600MHz ensures fast and efficient data processing, while the 7168 shading units and 204MB of L2 cache contribute to the GPU's overall performance and responsiveness.
In terms of raw power, the Max 1100 delivers an astounding theoretical performance of 22.22 TFLOPS, making it ideal for data center workloads such as machine learning, AI, and high-performance computing. The base clock of 1000MHz, boost clock of 1550MHz, and a TDP of 300W further solidify its reputation as a high-performance GPU.
In real-world usage, the Intel Data Center GPU Max 1100 excels in handling complex simulations, deep learning training, and other compute-intensive tasks. Its power-efficient design and advanced cooling solutions make it suitable for deployment in data centers without compromising on performance.
Overall, the Intel Data Center GPU Max 1100 is a powerhouse GPU that offers exceptional performance, reliability, and efficiency for data center workloads. Whether it's for AI research, scientific simulations, or data analytics, this GPU is an excellent choice for organizations seeking top-tier performance in a professional-grade package.
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Basic
Label Name
Intel
Platform
Professional
Launch Date
January 2023
Model Name
Data Center GPU Max 1100
Generation
Data Center GPU
Base Clock
1000MHz
Boost Clock
1550MHz
Bus Interface
PCIe 5.0 x16
Transistors
100,000 million
RT Cores
56
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.
448
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.
448
Foundry
Intel
Process Size
10 nm
Architecture
Generation 12.5
Memory Specifications
Memory Size
48GB
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
600MHz
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
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.
694.4 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.
22.22 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.
22.22 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.
21.776
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.
7168
L1 Cache
64 KB (per EU)
L2 Cache
204MB
TDP
300W
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 12-pin
Shader Model
6.6
Suggested PSU
700W
Benchmarks
FP32 (float)
Score
21.776
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS