Higher Education and Research Developer Resources
A hub of resources and news for educators and researchers.
Opportunities for Teaching and Research
Teaching Kits
NVIDIA Deep Learning Institute (DLI) Teaching Kits provide qualified educators with complete course solutions in deep learning, accelerated computing, and robotics. Bridge academic theory with real-world applications to empower next-generation innovators with critical AI skill sets.
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Certified Instructor Program
Experienced educators can get certified as Deep Learning Ambassadors and deliver hands-on DLI workshops to university faculty, students, and researchers at no cost.
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EDU Kits and Preferred Pricing
To better enable faculty, students, and researchers, NVIDIA makes state-of-the-art computing platforms accessible to academia to enable next GPU-accelerated apps, services, and algorithms.
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Studio Education Partners
The NVIDIA Studio Education Partner Program brings the latest advances in visual storytelling to the next generation of creative professionals. Prepare digital media students with technology experiences that directly translate to work in the industry.
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The NVIDIA Hardware Grant Program
The NVIDIA Hardware Grant Program promotes advances in artificial intelligence and data science by partnering with academic institutions around the world to enable researchers and educators with industry-leading hardware and software.
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Graduate Fellowships
PhD students are invited to submit their research projects for consideration to be part of the NVIDIA Graduate Fellowship Program.
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Jetson Community Project
Explore and learn from Jetson projects created by us and our community. These projects have been built for Jetson Nano, Jetson Xavier NX, Jetson TX2, and Jetson AGX Xavier.
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Applied Research Accelerator Program
The NVIDIA Applied Research Accelerator Program supports researchers with technical guidance, hardware, and funding for projects that can make real-world impact through deployment into GPU-accelerated applications.
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Accelerating AI Training with MLPerf Containers and Models from NVIDIA NGC
Deploying Real-time Object Detection Models with the NVIDIA Issac SDK and NVIDIA TAO Toolkit
Accelerating Deep Learning Research in Medical Imaging Using MONAI
Defining the Next Wave of GPU-Powered Research
Learn how a new AI computing cluster built using NVIDIA DGX-2™ systems at Oregon State University is enabling researchers to accelerate their work and publish cutting-edge advancements.
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Bringing GPU Computing to the Classroom
NVIDIA Teaching Kits lower the barrier of incorporating AI and GPU computing in coursework. Listen to NVIDIA’s higher education leadership and partners discuss opportunities for online training, certification, and cloud access to GPUs for teachers and students.
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How to Become an Ambassador for Deep Learning
Join NVIDIA’s higher education leadership and academic partners to learn how to get involved with the NVIDIA Deep Learning Institute (DLI) University Ambassador Program.
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PROGRAMS FOR YOU
Developer Resources
The NVIDIA Developer Program provides the advanced tools and training needed to successfully build applications on all NVIDIA technology platforms. This includes access to hundreds of SDKs, a network of like-minded developers through our community forums, and more.
Technical Training
NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, accelerated computing, and accelerated data science to solve real-world problems. Powered by GPUs in the cloud, training is available as self-paced, online courses or live, instructor-led workshops.
Accelerate Your Startup
NVIDIA Inception—an acceleration platform for AI, data science, and HPC startups—supports over 7,000 startups worldwide with go-to-market support, expertise, and technology. Startups get access to training through the DLI, preferred pricing on hardware, and invitations to exclusive networking events.
NVIDIA Higher Education and Research News
Programming Distributed Multi-GPU Tensor Operations with cuTENSOR v1.4
NVIDIA cuTENSOR library, v1.4, supports 64-dimensional tensors, distributed multi-GPU tensor ops, and improves tensor contraction performance models.
Implementing High Performance Matrix Multiplication Using CUTLASS v2.8
High performance CUTLASS template abstractions support matrix multiply operations (GEMM), Convolution AI, and improved Strided-DGrad.
Overcoming Advanced Computing Challenges with Million-X Performance
Learn more about the many ways scientists are applying advancements in Million-X computing and solving global challenges.
Accelerating ReLu and GeLu Activation Functions, and Batched Sparse GEMM in cuSPARSELt v0.2.0
NVIDIA cuSPARSELt v0.2 now supports ReLu and GeLu activation functions, bias vector, and batched Sparse GEMM.
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