high performance computing on graphics processing units: hgpu.org

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Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang

Nick Brown, Maurice Jamieson, Anton Lydike, Emilien Bauer, Tobias Grosser

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Tags: Computer science, Fortran, HPC, LLVM, MPI, nVidia, Package, Performance, Tesla V100

October 8, 2023 by hgpu

Advancing the distributed Multi-GPU ChASE library through algorithm optimization and NCCL library

Xinzhe Wu, Edoardo Di Napoli

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Tags: Algorithm optimization, Computer science, CUDA, MPI, nVidia, nVidia A100, OpenMP, OpenMPI, Package

October 8, 2023 by hgpu

Automated Buffer Sizing of Dataflow Applications in a High-Level Synthesis Workflow

Alexandre Honorat, Mickaël Dardaillon, Hugo Miomandre, Jean-François Nezan

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Tags: Code generation, Computer science, FPGA, HLS, OpenCL, Package, Performance

October 8, 2023 by hgpu

Impacts of Parallel Programming on Limited-Resource Hardware

Renato Barreto Hoffmann Filho

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming techniques, Thesis

October 8, 2023 by hgpu

Memory Efficient Mixed-Precision Optimizers

Basile Lewandowski, Atli Kosson

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Tags: Computer science, CUDA, Machine learning, Mixed precision, nVidia, nVidia A100, nVidia V100

October 1, 2023 by hgpu

OpenMP Kernel Language Extensions for Performance Portable GPU Codes

Shilei Tian, Tom Scogland, Barbara Chapman, Johannes Doerfert

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Tags: AMD Radeon Instinct MI250, ATI, Benchmarking, Compilers, Computer science, CUDA, HIP, nVidia, nVidia A100, OpenMP, performance portability

October 1, 2023 by hgpu

Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code Generation

Juan Fumero Alfonso, György Rethy, Athanasios Stratikopoulos, Nikolaos Foutris, Christos-Efthymios Kotselidis

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Tags: Code generation, Computer science, Heterogeneous systems, Java, OpenCL, Package

October 1, 2023 by hgpu

Novel Parallelization Strategies for High-Performance DNN Training on HPC Systems

Arpan Jain

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Tags: Artificial intelligence, Computer science, CUDA, Data parallelism, Deep learning, HPC, Machine learning, MPI, Neural networks, nVidia, Speech recognition, Tesla K80, Tesla V100, Thesis

October 1, 2023 by hgpu

Compressed Real Numbers for AI: a case-study using a RISC-V CPU

Federico Rossi, Marco Cococcioni, Roger Ferrer Ibàñez, Jesùs Labarta, Filippo Mantovani, Marc Casas, Emanuele Ruffaldi, Sergio Saponara

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Tags: AI, Compression, Computer science, Machine learning, Neural networks

September 24, 2023 by hgpu

Compiler-assisted distribution of OpenMP code for improved scalability

Jannek Squar

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Tags: Compression, Computer science, Heterogeneous systems, LLVM, MPI, OpenMP, Package, Thesis

September 24, 2023 by hgpu

Julia as a unifying end-to-end workflow language on the Frontier exascale system

William F. Godoy, Pedro Valero-Lara, Caira Anderson, Katrina W. Lee, Ana Gainaru, Rafael Ferreira da Silva, Jeffrey S. Vetter

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, HIP, HPC, Julia, MPI, Package

September 24, 2023 by hgpu

Evaluating the performance portability of SYCL across CPUs and GPUs on bandwidth-bound applications

Istvan Z Reguly

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, cfd, Computer science, CUDA, Fluid dynamics, HIP, Intel, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, OpenCL, performance portability, SYCL

September 24, 2023 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

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

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

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high performance computing on graphics processing units: hgpu.org

Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang

Advancing the distributed Multi-GPU ChASE library through algorithm optimization and NCCL library

Automated Buffer Sizing of Dataflow Applications in a High-Level Synthesis Workflow

Impacts of Parallel Programming on Limited-Resource Hardware

Memory Efficient Mixed-Precision Optimizers

OpenMP Kernel Language Extensions for Performance Portable GPU Codes

Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code Generation

Novel Parallelization Strategies for High-Performance DNN Training on HPC Systems

Compressed Real Numbers for AI: a case-study using a RISC-V CPU

Compiler-assisted distribution of OpenMP code for improved scalability

Julia as a unifying end-to-end workflow language on the Frontier exascale system

Evaluating the performance portability of SYCL across CPUs and GPUs on bandwidth-bound applications

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

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

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

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

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

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

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