CUDA Math Libraries Intern

NVIDIA is looking for software engineering interns for our teams which develop accelerated mathematical and data processing libraries like cuSparse, cuBLAS, cuSOLVER, cuFFT, nvImgCodec, nvComp, nvmath-python or DALI, that are a key part of high-performance computing and deep learning software stacks. The main purpose of these libraries is to provide the fastest primitives for linear algebra (dense and sparse), quantum computing and computer vision. Does the idea of being at the heart of these projects and applying your knowledge to make an impact around world sound exciting? If yes, then come and join our team!

In this role you will be part of our team responsible for the development of libraries that provide groundbreaking functionality and performance. The internship may include extending the capabilities of existing as well as building new libraries that will be used in various AI and HPC applications. It will involve working with senior software engineers who will provide mentorship and guidance. The project will include implementing new algorithms, defining APIs, analyzing performance, finding appropriate solutions for difficult numerical corner cases, and other general software engineering work.

What you’ll be doing:

• Collaborate with team members to understand software use cases and requirements

• Analyze the performance of GPU or CPU implementations and find opportunities for improvements

• Prototype and develop algorithms for single node and multi GPU clusters

What we need to see:

• Studying towards a MS or PhD degree in Computational Science, Computer Science, Applied Mathematics, Engineering, or a related field.

• Programming skills (C/C++, Python)

• Parallel or GPU programming experience (AVX, NEON, OpenMP, MPI, SHMEM, CUDA or OpenCL)

Ways to stand out from the crowd:

• Exposure to floating-point arithmetic and numerical error analysis.

• Knowledge of GPU/CPU and network hardware architecture.

• Understanding of composability and fusions, compilers, and implementation of programming languages

• Experience implementing sparse or dense linear algebra algorithms.

• Experience with domain-specific language design and compiler optimizations, in particular sparse compilers (MLIR or TACO)

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous, and love a challenge, we want to hear from you!

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