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When deploying GPUs in a high-performance computing (HPC) environment, customers face substantial obstacles and inefficiencies caused by the need to port and refactor code. Their efforts are further hampered by proprietary GPU programming environments that prohibit portability between GPU vendors and often result in inconsistency between CPU and GPU implementations. The need for GPU-level memory bandwidth, at scale, and sharing code investments between CPUs and GPUs for running a majority of the workloads in a highly parallelized environment has become essential.Â
Intel Data Center GPU Max Series is designed for breakthrough performance in data-intensive computing models used in AI and HPC.
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Financing available through HPEFS
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AI models continuously require larger data sets for more effective training. The faster you can process the data, the faster you can train and deploy the model.
The GPU accelerates end-to-end AI and data analytics pipelines with libraries optimized for Intel architectures and configurations tuned for HPC and AI workloads, high-capacity storage and high-bandwidth memory.
Common, open, standards-based programming model
Intel oneAPI is a common, open, standards-based programming model to unleash productivity and performance. Intel oneAPI tools include advanced compilers, libraries, profilers and code migration tools to easily migrate CUDA code to open C++ with SYCL.
Using oneAPI optimized deep learning frameworks and machine learning libraries, developers can realize drop-in acceleration for data analytics and machine learning workflows.
This easy-to-deploy, open-standards approach reduces development time, complexity and cost, and enables developers to overcome the constraints of proprietary environments that limit code portability.
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