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A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression

Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao

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Tags: Compression, Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla V100

November 22, 2020 by hgpu

Ginkgo – A Math Library designed for Platform Portability

Terry Cojean, Yu-Hsiang "Mike" Tsai, Hartwig Anzt

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Tags: Computer science, CUDA, HIP, nVidia, Package, Performance, performance portability

November 22, 2020 by hgpu

GPURepair: Automated Repair of GPU Kernels

Saurabh Joshi, Gautam Muduganti

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Tags: Computer science, CUDA, OpenCL, Package, Software Engineering

November 22, 2020 by hgpu

Adaptive Data Migration in Load-Imbalanced HPC Applications

Parsa Amini

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, load balancing, nVidia, Package, Tesla P100, Tesla V100, Thesis

November 15, 2020 by hgpu

Runtime Performances Benchmark for Knowledge Graph Embedding Methods

Angelica Sofia Valeriani

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Tags: Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 960, Package

November 15, 2020 by hgpu

Exploring the acceleration of Nekbone on reconfigurable architectures

Nick Brown

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Tags: Computer science, FPGA, HLS, nVidia, OpenCL, Tesla V100

November 15, 2020 by hgpu

Automatic GPU optimization through higher-order functions in functional languages

John Wikman

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Tags: Computer science, CUDA, nVidia, nVidia Quadro P 2000, Optimization, Thesis

November 15, 2020 by hgpu

Design and Performance Evaluation of Optimizations for OpenCL FPGA Kernels

Anthony M. Cabrera, Roger D. Chamberlain

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Tags: Computer science, FPGA, HLS, OpenCL, Optimization, Performance

November 8, 2020 by hgpu

Transparent Compiler and Runtime Specializations for Accelerating Managed Languages on FPGAs

Michail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos, Foivos S. Zakkak, Christos Kotselidis

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Tags: Computer science, FPGA, HLS, Java, OpenCL, Optimization, Package, Programming Languages

November 8, 2020 by hgpu

AMGCL – A C++ library for efficient solution of large sparse linear systems

Denis Demidov

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Tags: Computer science, CUDA, Mathematical Software, MPI, OpenCL, Package, Sparse, Sparse linear iterative solvers

November 8, 2020 by hgpu

TopicBERT for Energy Efficient Document Classification

Yatin Chaudhary, Pankaj Gupta, Khushbu Saxena, Vivek Kulkarni, Thomas Runkler, Hinrich Schütze

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Tags: classification, Computer science, CUDA, Deep learning, NLP, nVidia, Tesla T4

November 8, 2020 by hgpu

Tinker-HP: Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems

Olivier Adjoua, Louis Lagardère, Luc-Henri Jolly, Arnaud Durocher, Thibaut Very, Isabelle Dupays, Zhi Wang, Théo Jaffrelot Inizan, Frédéric Célerse, Pengyu Ren, Jay W. Ponder, Jean-Philip Piquemal

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Tags: Biophysics, Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia DGX-A100, OpenACC, Package, Physics, Tesla V100

November 8, 2020 by hgpu

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

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