N-Ways to GPU Programming Bootcamp

Easier, quicker command-line CUDA profiling

N-Ways to Multi-GPU Programming

Profiling with NVIDIA Nsight Tools Bootcamp

N-Ways to GPU Programming Bootcamp

Julia tools for NVIDIA Nsight Systems

References content from the OLCF CUDA Training Series. (https://github.com/olcf/cuda-training-series)

Reproducible Pascal GPU Unified Memory benchmark with Nsight and nvprof profiling

Lecture slides and exercise files of the CUDA 4 Dummies course (2025)

Profile-first ML systems project optimizing a multi-camera end-to-end driving model for hardware efficiency using PyTorch, CUDA streams, NVTX instrumentation, and Nsight Systems.

Real-time CUDA physics engine for N-body gravity, SPH fluids, and rigid-body collisions. Uses shared-memory tiling, kernel fusion, and spatial hashing on RTX 4080/4090.

Profiling with Precision. Documenting with Style.

libHPC is a high-performance computing library focused on Linux and Windows environments. It provides SIMD-optimized kernels, concurrent data structures, GPU utilities, and HPC-oriented memory management components.

This project demonstrates the integration of a CUDA kernel within an NVIDIA Holoscan application. It consists of two custom operators: one for memory allocation and data initialization, and another for executing the CUDA kernel. The application was profiled using Nsight systems and the kernel with Nsight compute

A systematic framework for studying MoE inference optimization strategies including expert-aware batching, expert placement (co-located vs. distributed), and scaling analysis across single-GPU, multi-GPU, and multi-node configurations.