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Multilayered Abstractions for Partial Differential Equations

Graham Robert Markall

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Code generation, CUDA, Differential equations, FEM, Finite element method, Mathematics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Partial differential equations, PDEs, Software Engineering, Thesis

December 11, 2013 by hgpu

A Methodology for Translating C-Programs to OpenCL

Krishnahari Thouti, S. R. Sathe

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, Programming Languages

November 16, 2013 by hgpu

SAGE: Self-Tuning Approximation for Graphics Engines

Mehrzad Samadi, Janghaeng Lee, D. Anoushe Jamshidi, Amir Hormati, Scott Mahlke

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Tags: Algorithms, Code generation, Compilers, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 560, Performance

November 14, 2013 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

Automatic Synthesis of Heterogeneous CPU-GPU Embedded Applications from a UML Profile

Federico Ciccozzi

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia

November 8, 2013 by hgpu

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Federico Ciccozzi

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia

October 18, 2013 by hgpu

Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Tiark Rompf, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Tesla C2050

October 15, 2013 by hgpu

Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs

Akihiro Hayashi, Max Grossman, Jisheng Zhao, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Computer science, Java, nVidia, OpenCL, Tesla M2050

October 5, 2013 by hgpu

Parametric GPU Code Generation for Affine Loop Programs

Athanasios Konstantinidis, Paul H. J. Kelly, J. Ramanujam, P. Sadayappan

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 580, OpenCL, Package, Tesla K20, Tesla M2070

October 5, 2013 by hgpu

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Jun Liu

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Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, nVidia, Tesla C2050, Thesis

October 3, 2013 by hgpu

Kokkos: Enabling performance portability across manycore architectures

H. Carter Edwards, Christian R. Trott

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Tags: Code generation, Computer science, CUDA, Intel Phi, Molecular dynamics, nVidia, Package, Tesla K20

September 17, 2013 by hgpu

Automatic Skeleton-Based Compilation through Integration with an Algorithm Classification

Cedric Nugteren, Pieter Custers, Henk Corporaal

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL, OpenMP

August 7, 2013 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Multilayered Abstractions for Partial Differential Equations

A Methodology for Translating C-Programs to OpenCL

SAGE: Self-Tuning Approximation for Graphics Engines

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Automatic Synthesis of Heterogeneous CPU-GPU Embedded Applications from a UML Profile

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Domain-Specific Languages for Heterogeneous Parallel Computing

Speculative Execution of Parallel Programs with Precise Exception Semantics on GPUs

Parametric GPU Code Generation for Affine Loop Programs

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Kokkos: Enabling performance portability across manycore architectures

Automatic Skeleton-Based Compilation through Integration with an Algorithm Classification

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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