high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference

Taesu Kim, Jongho Lee, Daehyun Ahn, Sarang Kim, Jiwoong Choi, Minkyu Kim, Hyungjun Kim

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Tags: Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Mixed precision, nVidia, nVidia A100, nVidia GeForce RTX 4090, nVidia RTX A6000, Package

February 18, 2024 by hgpu

Training DNN Models over Heterogeneous Clusters with Optimal Performance

Chengyi Nie, Jessica Maghakian, Zhenhua Liu

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, load balancing, Neural networks, nVidia, nVidia RTX 6000 Ada

February 12, 2024 by hgpu

Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs

Gianmarco Accordi, Davide Gadioli, Emanele Vitali, Luigi Crisci, Biagio Cosenza, Andrea Beccari, Gianluca Palermo

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Tags: Computer science, CUDA, HPC, molecular docking, nVidia, nVidia A100, oneAPI, Performance, SYCL

February 12, 2024 by hgpu

Gallatin: A General-Purpose GPU Memory Manager

Hunter McCoy, Prashant Pandey

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Tags: Computer science, CUDA, HPC, Memory, nVidia, nVidia A40, Package

February 4, 2024 by hgpu

Deductive verification for SYCL

Ellen Wittingen

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Tags: Computer science, CUDA, Heterogeneous systems, HIP, nVidia, OpenCL, OpenMP, Package, SYCL, Thesis

February 4, 2024 by hgpu

Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core

Robert Jendersie, Christian Lessig, Thomas Richter

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Tags: Computer science, CUDA, Earth and Space Sciences, Finite element method, Numerical Analysis, nVidia, nVidia A100, nVidia GeForce RTX 3090, OpenMP, Package, PyTorch, SYCL

February 4, 2024 by hgpu

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Andrea Montessori, Michele La Rocca, Giorgio Amati, Marco Lauricella, Adriano Tiribocchi, Sauro Succi

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Tags: cfd, CUDA, Fluid dynamics, HPC, Lattice Boltzmann model, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

February 4, 2024 by hgpu

LeftoverLocals: Listening to LLM Responses Through Leaked GPU Local Memory

Tyler Sorensen, Heidy Khlaaf

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Tags: Computer science, Data recovery, nVidia, nVidia GeForce RTX 4070, OpenCL, Package, Security, Vulkan

February 4, 2024 by hgpu

Assessing the Impact of Compiler Optimizations on GPUs Reliability

Fernando Fernandes dos Santos, Luigi Carro, Flavio Vella, Paolo Rech

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan V, PTX, Tesla K40, Tesla V100

January 28, 2024 by hgpu

BANG: Billion-Scale Approximate Nearest Neighbor Search using a Single GPU

Karthik V., Saim Khan, Somesh Singh, Harsha Vardhan Simhadri, Jyothi Vedurada

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Tags: Computer science, CUDA, Nearest neighbour, nVidia, nVidia A100

January 28, 2024 by hgpu

A Heterogeneous Inference Framework for a Deep Neural Network

Rafael Gadea-Gironés, José Luís Rocabado-Rocha, Jorge Fe, Jose M. Monzo

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Heterogeneous systems, HLS, Machine learning, Neural networks, OpenCL, PyTorch

January 28, 2024 by hgpu

Lessons Learned Migrating CUDA to SYCL: A HEP Case Study with ROOT RDataFrame

Jolly Chen, Monica Dessole, Ana Lucia Varbanescu

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Tags: CUDA, HEP, nVidia, nVidia Quadro RTX 4000, OpenCL, Package, Performance, Physics, SYCL

January 28, 2024 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference

Training DNN Models over Heterogeneous Clusters with Optimal Performance

Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs

Gallatin: A General-Purpose GPU Memory Manager

Deductive verification for SYCL

Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

LeftoverLocals: Listening to LLM Responses Through Leaked GPU Local Memory

Assessing the Impact of Compiler Optimizations on GPUs Reliability

BANG: Billion-Scale Approximate Nearest Neighbor Search using a Single GPU

A Heterogeneous Inference Framework for a Deep Neural Network

Lessons Learned Migrating CUDA to SYCL: A HEP Case Study with ROOT RDataFrame

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)