NVIDIA
Technology
SeniorSoftwareEngineer,CUTLASSPlatform
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, CUTLASS Platform at NVIDIA. Skills: GPU hardware features, Compiler backend, High performance kernels. Develop core CUTLASS platform components. Develop Tensor Core MMAs”
Industry & Context.
Debugging; Performance evaluation
What They're Looking For.
Must Have
Masters or PhD degree, 3+ years relevant industry experience, Proficiency in C++ programming, Software design experience, Debugging experience, Performance evaluation experience, Testing experience, High-performance code generation experience, Knowledge of compiler transformations, Knowledge of compiler optimizations, Deep understanding of computer architecture, Deep understanding of parallel computing programming models
Nice to Have
Experience writing low-level kernels, Hands-on compiler design experience, MLIR experience, Understanding of deep learning models, Understanding of deep learning algorithms, Understanding of deep learning frameworks
What You'll Do.
Develop core CUTLASS platform components
Develop Tensor Core MMAs
Develop synchronization barriers
Develop GPU hardware features
Contribute to MLIR-based backend compiler stack
Design compiler passes
Author example kernels
Showcase novel GPU hardware features
Collaborate with GPU architecture teams
Collaborate with CUDA teams
Collaborate with NVVM/PTX compiler teams
Provide feedback on programming models
Assess performance of future GPU hardware features
How You'll Work.
Team & Collaboration
GPU architecture teams; CUDA teams; NVVM/PTX compiler teams
Full Job Description
NVIDIA's high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, [_CUTLASS_](https://github.com/NVIDIA/cutlass) stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs. If you are passionate about designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ that enable writing high performance kernels, apply to join the CUTLASS team today! **What you 'll be doing:** * Develop core components of the CUTLASS platform including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features in CUDA C++ and CUTLASS Python DSL. * Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes. * Author example kernels utilizing CUTLASS abstractions to showcase the use of novel GPU hardware features that are crucial for achieving high performance. * Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features. **What we need to see:** * Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience). * 3+ years of relevant industry experience. * Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing. * Experience working with high-performance code generation and knowledge of compiler transformations and optimizations. * A deep understanding of computer architecture and parallel computing programming models. **Ways to stand out from the crowd:** * Experience writing high-performance kerne
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