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NVIDIA

Designs the chips and software that power AI

HPC Performance Engineer

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A Bachelor of Science, Master of Science, or equivalent experience in Computer Science or a related engineering field.
  • At least 5 years of programming experience.
  • A solid understanding of Fortran, C, C++, and programming techniques, especially for parallel architectures, preferably for compilers.
  • Experience with OpenACC, OpenMP, MPI, CUDA, and Standard Language Parallelism.
  • Strong skills in performance analysis and tuning, and a broad understanding of parallel application development tools and runtime environments.
  • Strong mathematical fundamentals, including linear algebra and numerical methods.
  • Understanding of performance considerations, tradeoffs, and impact.
  • Interpersonal skills, a logical approach to problem-solving, good time management, task prioritization, written and verbal communication skills, and the ability to work in a dynamic development team.

Responsibilities

  • Analyze the effect of different compilers and compiler optimizations on HPC application performance.
  • Evaluate whether and how the compiler and runtime can improve the performance of key HPC applications on CPU and CPU/GPU platforms.
  • Communicate limits of compiler capabilities with application engineering to guide the best path toward improving performance.
  • Port HPC applications to different platforms and programming models.
  • Evaluate the impact of NVHPC package components, device drivers, and system configuration on application performance.

Desired Qualifications

  • A deep understanding of machine architectures and micro-architectures.
  • Experience with debugging, porting, and assembly language programming.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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