Prototype and develop numerical algorithms for high-performance math libraries in the areas of dense and sparse linear algebra for single node and multi GPU clusters
Analyze the performance of GPU or CPU implementations and find opportunities for improvements.
Collaborate with team members to understand software use cases and requirements
What We Need To See
Studying towards a MS or PhD degree in Computer Science, Applied Math, Engineering, or related field.
Strong C++ programming, debugging, performance analysis, and test design skills.
Experience implementing sparse or dense linear algebra algorithms.
Parallel programming experience using CUDA, multi-threading or MPI.
Ways To Stand Out From The Crowd
Exposure to floating-point arithmetic and numerical error analysis.