GPU Kernel Dev & Perf Analysis Architect

1 Month ago • 4 Years + • Research & Development

Job Summary

Job Description

NVIDIA seeks a GPU Kernel Dev & Perf Analysis Architect to design, develop, and optimize GEMM (General Matrix Multiply) kernels for new architectures. Responsibilities include implementing and fine-tuning kernels for optimal performance on NVIDIA GPUs, conducting in-depth performance analysis, identifying bottlenecks, optimizing resource utilization, and improving throughput and power efficiency. The role involves creating and maintaining workloads and micro-benchmarks, generating performance reports, and collaborating with architecture, software, and product teams. This position requires 4+ years of experience in GPU programming or performance optimization for DL applications, expertise in CUDA programming, and proficiency with performance profiling tools like NVIDIA Nsight.
Must have:
  • 4+ years GPU programming/DL optimization experience
  • GEMM kernel development and optimization
  • GPU kernel performance analysis and improvement
  • CUDA programming expertise
  • Proficiency with NVIDIA Nsight

Job Details

NVIDIA is developing processor and system architectures that accelerate machine learning, automotive and high performance computing (HPC) applications. We are seeking a strong candidate to do GEMM kernel development and performance analysis for NVIDIA's new architectures. Your work will play a critical role in shaping the future of deep learning hardware and software, ensuring optimal performance for next-generation AI applications.  This position offers the opportunity to make a meaningful impact in a fast-moving, technology focused company.

What you'll be doing:

  • Design, develop, and optimize GEMM (General Matrix Multiply) kernels for NVIDIA's new architectures.

  • Implement and fine-tune kernels to achieve optimal performance on NVIDIA GPUs.

  • Conduct in-depth performance analysis of GPU kernels, including GEMM and other critical operations.

  • Identify bottlenecks, optimize resource utilization, and improve throughput, and power efficiency

  • Create and maintain workloads and micro-benchmark suites to evaluate kernel performance across various hardware and software configurations.

  • Generate performance projections, comparisons, and detailed analysis reports for internal and external stakeholders.

  • Collaborate with architecture, software, and product teams to guide the development of next-generation deep learning hardware and software.

What we need to see:

  • 4+ years of industry experience in GPU programming or performance optimization for DL applications.

  • Hands-on experience in developing and optimizing GEMM (General Matrix Multiply) kernels.

  • Demonstrated experience in analyzing and improving the performance of GPU kernels, with measurable results (e.g., performance improvements, efficiency gains).

  • Expertise in CUDA programming for GPU acceleration.

  • Experience with performance profiling tools (e.g., NVIDIA Nsight).

  • Excellent communication skills, both written and verbal.

  • Strong organizational and time management abilities, with the ability to prioritize tasks effectively.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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