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NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Yao Wan, Yang He, Jian-Guo Zhang, Yulei Sui, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, Package, Programming Languages, Python, Video

December 13, 2020 by hgpu

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

Woosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun

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

December 13, 2020 by hgpu

Efficient code generation for hardware accelerators by refining partially specified implementation

Ulysse Beaugnon

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Tags: Algorithms, Code generation, Computer science, CUDA, Linear Algebra, nVidia, Optimization, Package, Thesis

December 13, 2020 by hgpu

Toward Accurate Platform-Aware Performance Modeling for Deep Neural Networks

Chuan-Chi Wang, Ying-Chiao Liao, Ming-Chang Kao, Wen-Yew Liang, Shih-Hao Hung

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Performance

December 6, 2020 by hgpu

Python Workflows on HPC Systems

Dominik Strassel, Philipp Reusch, Janis Keuper

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Tags: Computer science, CUDA, Deep learning, GPU cluster, HPC, Machine learning, nVidia, PC cluster, Python

December 6, 2020 by hgpu

High-Throughput Parallel Viterbi Decoder on GPU Tensor Cores

Alireza Mohammadidoost, Matin Hashemi

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Tags: Algorithms, Computer science, CUDA, nVidia, Signal processing, Tesla V100

December 6, 2020 by hgpu

Evaluating the Performance and Portability of Contemporary SYCL Implementations

Beau Johnston, Jeffrey S. Vetter, Josh Milthorpe

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Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, CUDA, Heterogeneous systems, HIP, Matrix multiplication, nVidia, OpenCL, Package, Performance, Tesla P100

November 29, 2020 by hgpu

BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs

Massimo Bernaschi, Pasqua D'Ambra, Dario Pasquini

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Tags: Computer science, CUDA, multigrid, nVidia, Package, Sparse linear iterative solver

November 29, 2020 by hgpu

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

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

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

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

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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high performance computing on graphics processing units: hgpu.org

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

Efficient code generation for hardware accelerators by refining partially specified implementation

Toward Accurate Platform-Aware Performance Modeling for Deep Neural Networks

Python Workflows on HPC Systems

High-Throughput Parallel Viterbi Decoder on GPU Tensor Cores

Evaluating the Performance and Portability of Contemporary SYCL Implementations

BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs

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

Ginkgo – A Math Library designed for Platform Portability

GPURepair: Automated Repair of GPU Kernels

Adaptive Data Migration in Load-Imbalanced HPC Applications

Recent source codes

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

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

TensorCorePTX: PTX Tensor Core GEMM Exploration

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

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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