AI & HPC Ecosystem Developer Resources

Intel collaborates with key members of the AI and high-performance computing (HPC) ecosystem to enable developers to get the most performance from their software, models, and libraries running on Intel® hardware. Explore resources and learn from Intel customers how to get the most value from Intel CPUs, GPUs, and AI accelerators.

Hugging Face*

Hugging Face* and Intel collaborate to build state-of-the-art hardware and software AI acceleration with transformer models. Intel's AI Tools, Intel® Neural Compressor, Intel® Distribution of OpenVINO™ toolkit, and SigOpt* accelerate the Hugging Face Optimum library.

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PyTorch* Foundation

Intel is honored to join the PyTorch* Foundation as a premier member. Intel's contributions to PyTorch started in 2018 with the vision to democratize access to AI through ubiquitous hardware and open software.

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Red Hat*

Collaborations between Red Hat* and Intel take advantage of AI Tools, OpenVINO toolkit, and the cnvrg.io* platform available in the Red Hat OpenShift* AI managed cloud service (a joint AI developer program).

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Microsoft*

Microsoft* and Intel use Intel's latest hardware and optimized AI software for advanced data and AI capabilities with Microsoft .NET, Microsoft Azure*, and Microsoft Nuance*. This results in significant improvements and potential cost efficiencies within developer communities.

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Argonne National Laboratory

Intel, Hewlett Packard Enterprise*, and Argonne National Laboratory collaborated to build Aurora, one of the fastest supercomputers on the planet, for AI and HPC researchers.

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Testimonials

56 Results
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Image for: Accenture
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Accenture clients improve their total cost of ownership and performance by using best-in-class hardware and software from Intel.
Image for: Aible
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Aible significantly improved the performance of their machine learning code to analyze larger datasets on the same size compute resources.
Image for: Alibaba Cloud
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Alibaba Cloud* and Intel collaborated to help customers accelerate their online service using Intel technology.
Image for: Anodot
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With Intel IPP, Anodot saw results of 127x faster training performance and 66% reduction in overall cost.
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Intel and Ansys worked together to fully optimize engineering simulation software on the latest computing platforms.
Image for: Arcvideo Tech
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Arcvideo Tech builds a high-performance media pipeline on Intel® Data Center GPU Flex Series GPU.
Image for: Argonne
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Code portability shows application performance improvements on Argonne's development systems using Intel® Data Center GPU Max Series.
Image for: Argonne National Laboratory
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Argonne National Laboratory sees encouraging early application performance results on development systems using Intel® Max Series products.
Image for: AskUI
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This collaboration with Intel centered on optimizing state-of-the-art computer vision models for the UI Automation tool.
Image for: ASUS
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Intel® software optimization tools enhanced performance in distributed machine learning environments without compromising data privacy.
Image for: Bilic
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This joint effort includes integrating an advanced AI model and co-creating a robust, intelligent system for fraud detection.
Image for: BioDataAnalysis GmbH
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BioDataAnalysis GmbH uses Intel® oneAPI Data Analytics Library (oneDAL) for supervised object labeling in biological image analysis.
Image for: Boston IT Solutions India
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Implementing Intel® tools delivered a significant decrease in power use for each AI application to meet sustainability goals for the future.
Image for: byteLAKE
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Intel® technologies helped byteLAKE optimize AI product performance and ensure consistency across edge devices, servers, and HPC infrastructures.
Image for: Deci.ai
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YOLO-NAS Pose brings real-time pose estimation to the forefront—perfect for applications demanding quick, accurate AI insights.
Image for: Delphai
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The Intel AI solution powered by oneAPI helped Delphai improve performance for its multilingual translation model by up to 6.25x.
Image for: Developer Resources from Intel and CERN
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For its ATLAS framework, CERN took advantage of the Intel® oneAPI model that supports multiarchitecture programming via C++ with SYCL.
Image for: Developer Resources from Intel and Ginkgo
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Ginkgo allows multiarchitecture, cross-vendor programming on the latest Intel® architectures.
Image for: Developer Resources from Intel and IIT Goa
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Indian Institute of Technology Goa used Intel tools to migrate a Poisson solver equation from CUDA to SYCL, leading to 1.9x performance improvement.
Image for: Developer Resources from Intel and INESC-ID
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Learn how INESC-ID and Intel are working together to develop and optimize of advanced, scalable bioinformatics code for epistasis detection.
Image for: Developer Resources from Intel and Isima
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Intel and Isima worked together to reduce time to value while optimizing for price and performance in the cloud.​
Image for: Developer Resources from Intel and Old Dominion University (ODU)
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Old Dominion University overcame vendor hardware lock-in by migrating PAGANI and m-CUBES from CUDA to SYCL using AI Tools from Intel.
Image for: Developer Resources from Intel and Tencent Cloud
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Tencent Cloud worked with Intel to develop TencentDB, which helps users set up, operate, and expand relational databases in the cloud.
Image for: Developer Resources from Intel and The University of Utah (UofU)
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The SCI at the University of Utah used Intel oneAPI tools to implement the NEON AOP color-blending algorithm using multi-vendor-supported SYCL.
Image for: Dive Solutions GmbH
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Dive achieved 1.5x speedup in vectorization using Intel® CPU and Intel® toolkits.
Image for: Durham University
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The added value and big promise behind oneAPI is that we get one programming model for all parts of the machine.
Image for: Ecosystem Resources from Intel and C-DAC
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The Centre for Development of Advanced Computing (C-DAC) used Intel® tools to migrate a code base for their seismic modeling application.
Image for: Ecosystem Resources from Intel and Dive Solutions
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Dive Solutions used Intel® toolkits to optimize its cloud-native fluid solver on the latest Intel® CPUs.
Image for: GE Healthcare Testimonial
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Using Intel® oneAPI Base Toolkit, GE Healthcare migrated code to SYCL for an ultrasound diagnostics solution that requires heavy processing.
Image for: Google Cloud Platform Service Testimonial
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Collaborating with Intel and using the Intel® HPC Toolkit has helped our customer engineers understand in depth of our customers' HPC workloads.
Image for: Guise AI
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Optimizing helps Guise AI better serve customer needs with powerful, AI-driven Predictive Maintenance and Intelligent Asset Management solutions.
Image for: Hewlett Packard Enterprise (HPE) Testimonial
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HPE continues a long-standing partnership with Intel and support of oneAPI to provide tools to speed up market delivery.
Image for: HippoScreen Neurotech
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HippoScreen uses Intel® software optimizations to accelerate AI model build times and build AI pipelines in an efficient and adaptable way.
Image for: Hugging Face
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Hugging Face makes advancements in AI accessible by using Intel® tools for peak CPU performance, faster model training, and advanced AI deployments.
Image for: IBM
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Intel and IBM's AI collaboration delivers significant performance gains for enterprises. Integrating optimizations led to quicker response times.
Image for: ICURO
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ICURO and Intel collaborate in robotics and visual analytical tools, achieving active deep learning and facilitating testing and benchmarking.
Image for: Interperformant Systems Ltd.
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Interperformant Systems optimized a manually coded algorithm using Intel VTune Profiler to identify problems in the code.
Image for: Katana Graph
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Katana Graph ran a 1.3-million-cell genomic analysis on an Intel® Xeon® Scalable processor twice as fast as its closest competitor.
Image for: L&T Technology Services
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With Intel, L&T Technology Services trained, optimized, and deployed a smaller, faster, and cheaper machine learning model on edge devices.
Image for: Leibniz Supercomputing Centre
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ECHO code models weather events around black holes. Its code is built around SYCL to fully use an Intel® Xeon® processor.
Image for: Max Planck Computing & Data Facility
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The Max Planck Computing and Data Facility (MPCDF) in collaboration with Intel engineers developed a SYCL back end for Intel GPUs.
Image for: Meituan
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Meituan increased end-to-end AI and machine learning application processing performance using Intel® Toolkits on Intel® Xeon® platforms.
Image for: Microsoft .NET
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Microsoft used oneDAL in ML.NET to accelerate AI and machine learning training and inference run times and up to 3x performance improvement.
Image for: Microsoft Azure
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By integrating Intel® AI optimizations on Intel CPUs, Microsoft Azure was able to accelerate development and deployment of machine learning workloads.
Image for: PaddlePaddle
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Training and inference with this AI deep learning framework delivered breakthrough performance on Intel® Xeon® processors with oneAPI technology.
Image for: Prediction Guard
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Using Intel® Gaudi™ 2 architecture improved efficiency and doubled throughput for AI and machine learning use cases.
Image for: PyTorch Foundation
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As a premier member, Intel brings extensive expertise and commitment to accelerate development and democratization of open source PyTorch.
Image for: Quanta Cloud Technology (QCT)
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Developers can access HPC and AI resources from a collaboration between Intel and QCT.
Image for: Red Hat
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The Intel® AI Developer Program uses Red Hat OpenShift Data Science and Intel AI software for intelligent applications to edge environments.
Image for: SankhyaSutra Labs
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Intel® toolkits helped integrate software development, profiling, and deployment into a seamless AI and machine learning workflow.
Image for: SAP
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Intel VTune Profiler has been an essential tool for the performance analysis and tuning of SAP HANA* on the latest Intel® architecture.
Image for: Seekr
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Seekr uses Intel® GPUs and Intel® Gaudi® 2 processors to train and serve at scale, large- and medium-size transformers for hybrid AI computing.
Image for: University of Birmingham
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Using Codeplay's oneAPI plug-ins to migrate SYCL code led to faster simulations and almost 90% strong scaling efficiency in flood modeling software.
Image for: XtalPi
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By using Intel® toolkits, instruction set optimization, and function substitution, XtalPi improved how its structure comparison tool performs.
Image for: YUAN High Tech
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YUAN built an optimized video processing platform using Intel® toolkits, Intel® Core™ processors, and OpenVINO™ toolkit for AI and machine learning.
Image for: Zoho Corp
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Zoho uses oneAPI components to address video quality challenges in video processing workloads for AI and machine learning.

 

 

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Footnotes & Disclaimers

†Intel does not control or audit third-party data. You should consult other sources to evaluate accuracy.

‡Case Study: Ningbo Konfoong Bioinformation Technology (KFBIO) Accelerates M. Tuberculosis Detection with Intel® AI