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

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Automating Heterogeneous Parallelism in Numerical Differential Equations

Dat3M: Memory Model Aware Verification

Towards Unified Analysis of GPU Consistency

NVIDIA Federated Learning Application Runtime Environment

Supercharging Federated Learning with Flower and NVIDIA FLARE

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

General-purpose Polyhedral Compilers

A Survey of General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

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high performance computing on graphics processing units: hgpu.org

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

COOK Access Control on an embedded Volta GPU

Fast and Practical Strassen’s Matrix Multiplication using FPGAs

Machine learning enhanced code optimization for high-level synthesis (ML-ECOHS)

Addressing Challenges in Utilizing GPUs for Accelerating Privacy-Preserving Computation

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

A Systematic Literature Survey of Sparse Matrix-Vector Multiplication

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

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

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

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