high performance computing on graphics processing units: hgpu.org

Massinissa Merouani, Khaled Afif Boudaoud, Iheb Nassim Aouadj, Nassim Tchoulak, Islam Kara Bernou, Hamza Benyamina, Fatima Benbouzid-Si Tayeb, Karima Benatchba, Hugh Leather, Riyadh Baghdadi

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Tags: Compilers, Computer science, Deep learning, Machine learning, OpenCL, Package, Programming Languages

March 24, 2024 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

OpenMP offload at the Exascale using Intel GPU Max 1550: evaluation of STREAmS compressible solver

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

High Performance Privacy Preserving AI

Speed, power and cost implications for GPU acceleration of Computational Fluid Dynamics on HPC systems

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

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

Seer: Predictive Runtime Kernel Selection for Irregular Problems

Using Intel oneAPI for Multi-hybrid Acceleration Programming with GPU and FPGA Coupling

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

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