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Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Moritz Schmid, Oliver Reiche, Christian Schmitt, Frank Hannig, Jurgen Teich

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Tags: ARM, Code generation, Compilers, Computational Complexity, Computer science, Differential equations, FPGA, Image processing, Partial differential equations, PDEs

August 23, 2014 by hgpu

Integrating Profiling into MDE Compilers

Vincent Aranega, A. Wendell O. Rodrigues, Anne Etien, Frederic Guyomarch, Jean-Luc Dekeyser

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Tags: Compilers, Computer science, nVidia, OpenCL, Tesla S1070, Tesla T10

August 3, 2014 by hgpu

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Peng Di

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tesla C2050, Thesis

July 30, 2014 by hgpu

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075, Tesla K20, Tesla M2050

July 28, 2014 by hgpu

ADHA: Automatic Data layout framework for Heterogeneous Architectures

Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar

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Tags: Benchmarking, Compilers, Computer science, Heterogeneous systems, nVidia, OpenCL, Programming Languages, Tesla M2050

July 24, 2014 by hgpu

COFFEE: an Optimizing Compiler for Finite Element Local Assembly

Fabio Luporini, Ana Lucia Varbanescu, Florian Rathgeber, Gheorghe-Teodor Bercea, J. Ramanujam, David A. Ham, Paul H.J. Kelly

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Tags: Compilers, Computer science, Differential equations, FEM, Finite element method, Intel Xeon Phi, Mathematical Software, Partial differential equations, PDEs

July 10, 2014 by hgpu

The Framework and Compilation Techniques for Directive-based GPU Cluster Programming

Pisit Makpaisit, Putchong Uthayopas

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Tags: Compilers, Computer science, CUDA, GPU cluster, nVidia, OpenACC, Tesla M2050

July 3, 2014 by hgpu

Developing a compiler for the XeonPhi

Paul Cockshott, Susanne Oehler, Tian Xu

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Tags: Compilers, Computer science, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, Performance

May 21, 2014 by hgpu

Automatic Scheduling of Compute Kernels Across Heterogeneous Architectures

Robert F. Lyerly

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Tags: Compilers, Computer science, Heterogeneous systems, Intel Xeon Phi, Machine learning, nVidia, OpenCL, OpenMP, Task scheduling, Tesla C2075

May 9, 2014 by hgpu

Accelerating Mixed-Abstraction SystemC Models on Multi-Core CPUs and GPUs

Anirudh Mohan Kaushik

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla C2075, Thesis

May 5, 2014 by hgpu

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Marcel Koster, Roland Leissa, and Sebastian Hack, Richard Membarth, Philipp Slusallek

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

January 26, 2014 by hgpu

Tesla vs. Xeon Phi vs. Radeon A Compiler Writer’s Perspective

Brent Leback, Douglas Miles, Michael Wolfe

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Tags: ATI, Compilers, Computer science, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla

December 18, 2013 by hgpu

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

No More Shading Languages: Compiling C++ to Vulkan Shaders

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high performance computing on graphics processing units: hgpu.org

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Integrating Profiling into MDE Compilers

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

ADHA: Automatic Data layout framework for Heterogeneous Architectures

COFFEE: an Optimizing Compiler for Finite Element Local Assembly

The Framework and Compilation Techniques for Directive-based GPU Cluster Programming

Developing a compiler for the XeonPhi

Automatic Scheduling of Compute Kernels Across Heterogeneous Architectures

Accelerating Mixed-Abstraction SystemC Models on Multi-Core CPUs and GPUs

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Tesla vs. Xeon Phi vs. Radeon A Compiler Writer’s Perspective

Recent source codes

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

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