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hgpu.org » Applications » Computer science

Synthesizing Benchmarks for Predictive Modeling

Chris Cummins, Pavlos Petoumenos, Zheng Wang, Hugh Leather

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Compilers, Computer science, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan, OpenCL, Package

December 31, 2016 by hgpu

Automatic OpenCL Task Adaptation for Heterogeneous Architectures

Pierre Huchant, Marie-Christine Counilh, Denis Barthou

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Tags: Compilers, Computer science, Heterogeneous systems, nVidia, nVidia Quadro K5000, OpenCL, Tesla K20, Tesla M2075

December 31, 2016 by hgpu

Android Malware Classification Using Parallelized Machine Learning Methods

Lifan Xu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, OpenMP, Security, Tesla C2050, Thesis

December 31, 2016 by hgpu

dOpenCL – Evaluation of an API-Forwarding Implementation

Karsten Tausche, Max Plauth, Andreas Polze

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Tags: Computer science, Distributed computing, MPI, OpenCL, Package, Virtualization

December 31, 2016 by hgpu

Function Call Re-Vectorization

Rubens E. A. Moreira, Sylvain Collange, Fernando Magno Quintao Pereira

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Package, String matching

December 26, 2016 by hgpu

Language Modeling with Gated Convolutional Networks

Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, Performance, Tesla M40, Torch

December 26, 2016 by hgpu

Batched Shift Reduce Parsing with Lists of Vectors on CUDA

Andrew Drozdov

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Tags: Computer science, CUDA, Deep learning, NLP, nVidia, nVidia GeForce GTX Titan Black, Package, Torch

December 26, 2016 by hgpu

Streaming GPU Singular Value and Dynamic Mode Decompositions

Seth D. Pendergrass, J. Nathan Kutz, Steven L. Brunton

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Tags: Algorithms, Computer vision, CUDA, Mathematics, Matrix multiplication, Numerical Analysis, nVidia, Sparse matrix, Tesla K40

December 26, 2016 by hgpu

High productivity multi-device exploitation with the Heterogeneous Programming Library

Moises Vinas, Basilio B. Fraguela, Diego Andrade, Ramon Doallo

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, load balancing, nVidia, OpenCL, Package, Portability, Tesla K20, Tesla M2050

December 22, 2016 by hgpu

Log File Regular Expression Pattern Matching And Capture With GPUs

António Luís Pinto Silva

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 850 M, Package, pattern matching, Thesis

December 22, 2016 by xhgpu

Performance Optimisation of Smoothed Particle Hydrodynamics Algorithms for Multi/Many-Core Architectures

Fabio Baruffa, Luigi Iapichino, Nicolay J. Hammer, Vasileios Karakasis

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Tags: Algorithms, Astrophysics, Computational Physics, Computer science, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, OpenMP, Performance, Physics

December 20, 2016 by hgpu

Accelerating Spark RDD Operations with Local and Remote GPU Devices

Yasuhiro Ohno, Shin Morishima, Hiroki Matsutani

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 980 Ti, Spark

December 20, 2016 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

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

CANNBot Skills

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

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high performance computing on graphics processing units: hgpu.org

Applications

Synthesizing Benchmarks for Predictive Modeling

Automatic OpenCL Task Adaptation for Heterogeneous Architectures

Android Malware Classification Using Parallelized Machine Learning Methods

dOpenCL – Evaluation of an API-Forwarding Implementation

Function Call Re-Vectorization

Language Modeling with Gated Convolutional Networks

Batched Shift Reduce Parsing with Lists of Vectors on CUDA

Streaming GPU Singular Value and Dynamic Mode Decompositions

High productivity multi-device exploitation with the Heterogeneous Programming Library

Log File Regular Expression Pattern Matching And Capture With GPUs

Performance Optimisation of Smoothed Particle Hydrodynamics Algorithms for Multi/Many-Core Architectures

Accelerating Spark RDD Operations with Local and Remote GPU Devices

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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

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