Leopold Cambier

Leopold Cambier received his Ph.D. in computational and mathematical engineering from Stanford University in 2021, working on fast solvers for large sparse linear systems. He also interned at NVIDIA in the cuDNN team in 2016 and 2017. Since he joined full-time in January 2021, Leopold has been working on distributed FFTs, device libraries, kernel heuristics and Python interop.
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Posts by Leopold Cambier

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Developer Tools & Techniques Jul 30, 2026

Run High-Performance Core Math at Scale with NVIDIA nvmath-python

NVIDIA nvmath-python is a library designed to bridge the gap between the Python scientific community and NVIDIA CUDA-X math libraries. It gives Python users... 15 MIN READ
Developer Tools & Techniques Sep 02, 2025

Improving GEMM Kernel Auto-Tuning Efficiency on NVIDIA GPUs with Heuristics and CUTLASS 4.2

Selecting the best possible General Matrix Multiplication (GEMM) kernel for a specific problem and hardware is a significant challenge. The performance of a... 8 MIN READ
Robotics Dec 14, 2024

Introducing Tile-Based Programming in Warp 1.5.0

With the latest release of Warp 1.5.0, developers now have access to new tile-based programming primitives in Python. Leveraging cuBLASDx and cuFFTDx, these new... 14 MIN READ
Simulation / Modeling / Design Jan 27, 2022

Multinode Multi-GPU: Using NVIDIA cuFFTMp FFTs at Scale

Today, NVIDIA announces the release of cuFFTMp for Early Access (EA). cuFFTMp is a multi-node, multi-process extension to cuFFT that enables scientists and... 10 MIN READ