high performance computing on graphics processing units: hgpu.org

hgpu.org » Operating systems

LithOS: An Operating System for Efficient Machine Learning on GPUs

Patrick H. Coppock, Brian Zhang, Eliot H. Solomon, Vasilis Kypriotis, Leon Yang, Bikash Sharma, Dan Schatzberg, Todd C. Mowry, Dimitrios Skarlatos

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, nVidia, nVidia A100, nVidia H100, Operating systems

April 27, 2025 by hgpu

GPUVM: GPU-driven Unified Virtual Memory

Nurlan Nazaraliyev, Elaheh Sadredini, Nael Abu-Ghazaleh

View

Download (PDF)

Tags: Computer science, CUDA, Memory, nVidia, Operating systems, Performance, Tesla V100

November 17, 2024 by hgpu

Research and Development of Porting SYCL on QNX Operating System for High Parallelism

Dengpan Wang

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Operating systems, PTX, SYCL, Thesis

January 16, 2022 by hgpu

On Runtime Systems for Task-based Programming on Heterogeneous Platforms

Samuel Thibault

View

Download (PDF)

Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Operating systems, StarPU, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075, Thesis

December 23, 2018 by hgpu

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Waqar Ali, Heechul Yun

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia Jetson TK1, Operating systems, Performance, Security, SoC

December 28, 2017 by hgpu

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

Carlos Arango, Remy Dernat, John Sanabria

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, Operating systems, Package, Performance, Tesla K20, Virtualization

October 3, 2017 by hgpu

Parallel and in-process compilation of individuals for genetic programming on GPU

Hakan Ayral, Songul Albayrak

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GRID K520, Operating systems, Package

May 24, 2017 by hgpu

GPU System Call

Jan Vesely, Arkaprava Basu, Abhishek Bhattacharjee, Gabriel Loh, Mark Oskin, Steven K. Reinhardt

View

Download (PDF)

Tags: ATI, C++ AMP, Computer science, Operating systems

May 22, 2017 by hgpu

A Runtime Controller for OpenCL Applications on Heterogeneous System Architectures

Cristiana Bolchini, Stefano Cherubin, Gianluca C. Durelli, Simone Libutti, Antonio Miele, Marco D. Santambrogio

View

Download (PDF)

Tags: ARM, Computer science, Heterogeneous systems, OpenCL, Operating systems

October 8, 2016 by hgpu

TREES: A CPU/GPU Task-Parallel Runtime with Explicit Epoch Synchronization

Blake A. Hechtman, Andrew D. Hilton, Daniel J. Sorin

View

Download (PDF)

Tags: AMD, APU, Computer science, OpenCL, Operating systems, Programming Languages

August 4, 2016 by hgpu

Vulnerable GPU Memory Management: Towards Recovering Raw Data from GPU

Zhe Zhou, Wenrui Diao, Xiangyu Liu, Zhou Li, Kehuan Zhang, Rui Liu

View

Download (PDF)

Tags: AMD Radeon R7 250, ATI, Cloud, Computer science, nVidia, nVidia GeForce GTX 750, OpenCL, Operating systems, Security

May 26, 2016 by hgpu

Reducing overheads of dynamic scheduling on heterogeneous chips

Francisco Corbera, Andres Rodriguez, Rafael Asenjo, Angeles Navarro, Antonio Vilches, Maria J. Garzaran

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, OpenCL, Operating systems

January 15, 2015 by hgpu

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

* * *

high performance computing on graphics processing units: hgpu.org

LithOS: An Operating System for Efficient Machine Learning on GPUs

GPUVM: GPU-driven Unified Virtual Memory

Research and Development of Porting SYCL on QNX Operating System for High Parallelism

On Runtime Systems for Task-based Programming on Heterogeneous Platforms

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

Parallel and in-process compilation of individuals for genetic programming on GPU

GPU System Call

A Runtime Controller for OpenCL Applications on Heterogeneous System Architectures

TREES: A CPU/GPU Task-Parallel Runtime with Explicit Epoch Synchronization

Reducing overheads of dynamic scheduling on heterogeneous chips

Recent source codes

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

Most viewed papers (last 30 days)