Intel Data Center GPU Max 1550
The Intel Data Center GPU Max 1550 is a powerful professional-grade GPU designed specifically for data center applications. With a base clock speed of 900MHz and a boost clock speed of 1600MHz, this GPU is capable of delivering exceptional performance for a wide range of tasks.
One of the standout features of the Max 1550 is its massive 128GB of HBM2e memory, which allows it to handle large datasets and complex workloads with ease. The memory clock speed of 1600MHz further enhances its ability to quickly access and manipulate data, making it a great choice for data analytics, machine learning, and other data-intensive tasks.
The GPU also boasts an impressive 16384 shading units, 408MB of L2 cache, and a TDP of 600W, all of which contribute to its ability to handle demanding workloads efficiently. With a theoretical performance of 52.43 TFLOPS, the Max 1550 is well-equipped to handle the most demanding computational tasks.
Overall, the Intel Data Center GPU Max 1550 is a high-performance and versatile GPU that is well-suited for data center applications. Its combination of powerful hardware specs and ample memory make it an excellent choice for organizations looking to accelerate their data-intensive workloads and maximize their overall computational efficiency.
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Basic
Label Name
Intel
Platform
Professional
Launch Date
January 2023
Model Name
Data Center GPU Max 1550
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
1600MHz
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.
3277 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
600W
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
1000W
Benchmarks
FP32 (float)
Score
51.381
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS