Senior HPC Performance Engineer
Indexed description
JR2016204
Job Category
Engineering
Time Type
Full time
As a member of our team in NVIDIA's NVHPC compilers & tools group, you will analyze and run High Performance Computing (HPC) applications on HPC servers and systems to gain insight into the performance characteristics of these applications. The applications you'll work with range from small synthetic benchmarks that use a single core to full applications that utilize all of the resources on distributed-memory systems with heterogeneous compute nodes including CPUs, GPUs and many-core processors. In this role you will analyze these applications and identify optimization opportunities for compiler development teams and application engineering teams.
What You’ll Be Doing
- Assist customers GPU accelerate HPC applications.
- Analyze High Performance Computing(HPC) applications to better understand their performance characteristics.
- Provide advise and drive compiler and applications engineering development teams based on the analysis of these HPC applications.
- BS/MS or equivalent experience in Computer Science or related engineering field.
- 8+ Years of programming experience.
- Solid understanding of Fortran/C/C++, as well as programming techniques, especially for parallel architectures; preferably for compilers
- Experience with OpenACC, OpenMP, MPI, and CUDA.
- Strong skills in performance analysis and tuning, as well as a broad understanding of parallel applications development tools and runtime environments.
- Strong mathematical fundamentals, including linear algebra and numerical methods.
- Understand performance considerations, tradeoffs and impact.
- Expert interpersonal skills, logical approach to problem solving, good time management and task prioritization skills. Excellent written and verbal communication skills.
- Strong communication skills are required along with the ability to work in a dynamic product oriented team.
- Experience is leading and/or management projects is a plus.
- You have a deep understanding of machine architectures and micro-architectures.
- Experience with debugging and porting as well as assembly language programming is a significant advantage.
NVIDIA's invention of the GPU revolutionized parallel computing. Our GPUs are being used in many of the largest high-performance computing projects around the world, solving real world problems. Our products are used to build and parallelize the most meaningful scientific applications for weather modeling, climatology, fluid dynamics and defense. We support real science and scientists throughout the world.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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