"Like a time machine, we make computers for the Einsteins and da Vincis of our time to help them see and create the future." (Jensen Huang, 2019 NVIDIA Annual Report)I’m privileged to lead the Higher Education/Research & HPC Solutions Architect team at NVIDIA where we’re bringing the game-changing technologies of accelerated computing and artificial intelligence (AI) together to tackle the largest research challenges of our time.Our team's mission is to help developers adopt the NVIDIA platform. As such we're a cross-functional team of external-facing scientists and engineers, interacting with business leaders, sales, developer relations, marketing, engineering, etc., to do whatever it takes to help our developers and customers be successful with the NVIDIA platform.We are equally at home digging into code, as we are presenting the NVIDIA platform to our customers and developers. We deal with the full stack, from servers and networking, to libraries and software, to frameworks and applications.

Part of a world-class team of Solutions Architects (customer-facing engineers) working with researchers to bring the latest technologies in artificial intelligence and GPU computing to bear in support of challenging problems at the cutting edge of scientific research.My primary focus is in Higher Education & Research, Life Sciences, HPC and Deep Learning.What I do:Support developers and customers as they deploy GPU computing solutions.Deliver hands-on GPU programming workshops at customer sites to teach GPU computing via GPU-enabled libraries, OpenACC compiler directives and the use of programming languages such as CUDA C/C++, as well as create content and teach at NVIDIA's Deep Learning Institute.Assist developers with performance optimization, hardware and software issues, debugging and general GPU programming inquiries.In summary, I'm a customer-facing engineer for all things related to GPU computing. It's extremely rewarding as I get to help our customers and developers utilize the power of GPU computing to solve the world's most pressing scientific and engineering questions.

Software Engineer in Scientific Libraries group. Scientific Libraries (aka Cray LibSci) is part of the Programming Environments division, dedicated to providing an easy and productive user and developer experience for HPC. Some of the things I did were: Design, develop, implement and maintain the custom high performance serial and parallel scientific libraries that Cray provides for customers. Worked on linear algebra software including BLAS and LAPACK. Also worked with FFT software including FFTW.Developed in MPI, C, Fortran, CUDA, and x86 assembly with specific focus on AMD Opteron CPUs and NVIDIA GPUs. Also shell scripting and languages such as Ruby for software infrastructure tasks.Customer benchmarking and code optimization tasks in support of the world's fastest machines deployed for open science research.Singular focus on writing libraries that extract the highest performance possible to achieve the ground-breaking research that Cray is known for.