*RRP - Reseller Recommend Price. Prices may vary based on local reseller.Prices provided in quotes by local resellers may vary.Show MoreShow Less
Loading...
https://connect.hpe.com/e/f2?nocache
en
Our system could not confirm your address to be valid and cannot find a recommended alternative. It is strongly recommended that you edit the address and try again. You may also continue with the address as you entered it if you are sure it is correct.
Provided User Id doesn't have access to this country, Please try sign in to authorized country partner portal.
Partner doesn’t have any country associated. Please contact System administrator.
Your Email/Password combination is incorrect. Please try again.
We've identified you as an Partner Store customer accessing HPE Storefront. Please 'click here' to log in to the Partner Store.
We've identified you as an HPE storefront customer accessing the Partner Store. Please 'click here' to log in to the HPE storefront.
Login Error
The requested account is an existing enterprise account. Please click here to login to enterprise store.
Sign-in Error
The associated account is connected to an employee profile. Please either register or use an alternative account to log in to the storefront.
Thank you for filling out your profile information. To complete your registration, please check your inbox for an email from Hewlett Packard Enterprise (HPE) and follow the validation steps.
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.
Intel Data Center GPU Max Series is designed for breakthrough performance in data-intensive computing models used in AI and HPC.
SKU #
S1T67C
Sold by:
HPE
Get Started
Financing available through HPEFS
Offered by HPE Reseller
Pricing displayed for the products does not include applicable taxes and shipping.
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.
{"baseProduct":{"productID":"S1T67C","productName":"Intel Xe Link Bridge for HPE"},"navigationList":["Options","Server Accelerators","Computational and Graphics Accelerators for Servers","Intel Accelerators for HPE","Intel Xe Link Bridge for HPE"],"cartDetail":{},"productInfo":[{"productInfo":{"quantity":"1","productID":"S1T67C","productName":"Intel Xe Link Bridge for HPE"}}]}
