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Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Weifeng Liu

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Tags: Algorithms, AMD Radeon R9 290X, ATI, Benchmarking, Computer science, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan Black, OpenCL, Sparse matrix, Thesis

February 16, 2016 by hgpu

Writing a performance-portable matrix multiplication

Jorge F. Fabeiro, Diego Andrade, Basilio B. Fraguela

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Tags: AMD FirePro S9150, ATI, Code generation, Computer science, Heterogeneous systems, Intel Xeon Phi, Matrix multiplication, nVidia, OpenCL, Package, Performance, performance portability, Tesla K20

February 11, 2016 by hgpu

Programming GPUs with C++14 and Just-In-Time Compilation

Michael Haidl, Bastian Hagedorn, Sergei Gorlatch

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Tags: Compilers, Computer science, CUDA, Intel Xeon Phi, LLVM, nVidia, OpenCL, PTX, Tesla K20

February 10, 2016 by hgpu

BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Matthieu Courbariaux, Yoshua Bengio

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Tags: Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 750, Package, Python

February 10, 2016 by hgpu

GPU-Accelerated High-Level Synthesis for Bitwidth Optimization of FPGA Datapaths

Nachiket Kapre, Deheng Ye

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Tags: Benchmarking, Code generation, Computer science, CUDA, FPGA, nVidia, Package, Performance, Tesla K20

February 10, 2016 by hgpu

FARGO3D: A new GPU-oriented MHD code

Pablo Benitez-Llambay, Frederic Masset

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Tags: Astrophysics, CUDA, Finite difference, Instrumentation and Methods for Astrophysics, Magnetohydrodynamics, MPI, N-body simulation, nVidia, Package, Physics, Tesla K20

February 10, 2016 by hgpu

Performance Portable GPU Code Generation for Matrix Multiplication

Toomas Remmelg, Thibaut Lutz, Michel Steuwer, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX Titan Black, OpenCL

February 10, 2016 by hgpu

Portable Programming Models for Heterogeneous Platforms

Deepak Majeti

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Tags: ATI, ATI Radeon HD 5970, ATI Radeon HD 7660, Computer science, Heterogeneous systems, nVidia, OpenCL, Package, Tesla M2050, Thesis

February 8, 2016 by hgpu

High performance high-order numerical methods: applications in ocean modeling

Rajesh Gandham

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Tags: ATI, ATI Radeon HD 7970, cfd, Computer science, CUDA, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTX Titan, OCCA, OpenCL, OpenMP, real time systems, Tesla C2050, Tesla K20, Tesla K40, Thesis

February 8, 2016 by hgpu

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

Weylin MacCalla, Sameer Kulkarni

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Tags: ATI, ATI Radeon HD 7850, cfd, Fluid dynamics, Fortran, nVidia, OpenACC, Tesla K40

February 8, 2016 by hgpu

Workload distribution and balancing in FPGAs and CPUs with OpenCL and TBB

Rafael Asenjo, Angeles Navarro, Andres Rodriguez, Jose Nunez-Yanez

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Tags: Computer science, FPGA, Heterogeneous systems, nVidia, nVidia Quadro K600, OpenCL

February 8, 2016 by hgpu

Integrating GPGPU computations with CPU coroutines in C++

Pavel A. Lebedev

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Tags: AMD Radeon R7 265, ATI, ATI Radeon HD 7570, CUDA, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 580, OpenCL, Physics

February 8, 2016 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Writing a performance-portable matrix multiplication

Programming GPUs with C++14 and Just-In-Time Compilation

BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

GPU-Accelerated High-Level Synthesis for Bitwidth Optimization of FPGA Datapaths

FARGO3D: A new GPU-oriented MHD code

Performance Portable GPU Code Generation for Matrix Multiplication

Portable Programming Models for Heterogeneous Platforms

High performance high-order numerical methods: applications in ocean modeling

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

Workload distribution and balancing in FPGAs and CPUs with OpenCL and TBB

Integrating GPGPU computations with CPU coroutines in C++

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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