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A Comprehensive Performance Analysis of HSA and OpenCL 2.0

Saoni Mukherjee, Yifan Sun, Paul Blinzer, Amir Kavyan Ziabari, David Kaeli

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Tags: Algorithms, ATI, Benchmarking, Computer science, Heterogeneous systems, OpenCL, Performance

August 8, 2016 by hgpu

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

Kevin L. Keys, Gary K. Chen, Kenneth Lange

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Tags: Bioinformatics, Genetics, Machine learning, nVidia, OpenCL, Package, Statistics, Tesla C2050

August 8, 2016 by hgpu

OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory

Maciej Wielgosz, Marcin Pietron

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Tags: Algorithms, AMD Radeon R9 390, ATI, Computer science, Computer vision, Machine learning, OpenCL, Package, PyOpenCL, Python

August 8, 2016 by hgpu

Daino: A High-level Framework for Parallel and Efficient AMR on GPUs

Mohamed Wahib, Naoya Maruyama, Takayuki Aoki

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Tags: Adaptive Mesh Refinement, CUDA

August 5, 2016 by wahibium

Parallel experiments with RARE-BLAS

Chemseddine Chohra, Philippe Langlois, David Parello

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Tags: Algorithms, BLAS, Computer science, Intel Xeon Phi, Linear Algebra

August 4, 2016 by hgpu

RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks

Patrick Doetsch, Albert Zeyer, Paul Voigtlaender, Ilya Kulikov, Ralf Schluter, Hermann Ney

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Package, RNN, Speech recognition

August 4, 2016 by hgpu

TREES: A CPU/GPU Task-Parallel Runtime with Explicit Epoch Synchronization

Blake A. Hechtman, Andrew D. Hilton, Daniel J. Sorin

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Tags: AMD, APU, Computer science, OpenCL, Operating systems, Programming Languages

August 4, 2016 by hgpu

A survey of sparse matrix-vector multiplication performance on large matrices

Max Grossman, Christopher Thiele, Mauricio Araya-Polo, Florian Frank, Faruk O. Alpak, Vivek Sarkar

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Tags: Computer science, CUDA, Linear Algebra, Numerical Analysis, nVidia, Performance, Sparse matrix, survey, Tesla M2070

August 4, 2016 by hgpu

Programming Embedded Manycore: Refinement and Optimizing Compilation of a Parallel Action Language for Hierarchical State Machines

Ivan Llopard

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Tags: Compilers, Computer science, OpenCL, Thesis

August 4, 2016 by hgpu

A Gb/s Parallel Block-based Viterbi Decoder for Convolutional Codes on GPU

Hao Peng, Rongke Liu, Yi Hou, Ling Zhao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 980, Signal processing

August 4, 2016 by hgpu

The ANTAREX Approach to Autotuning and Adaptivity for Energy Efficient HPC Systems

Cristina Silvano, Giovanni Agosta, Stefano Cherubin, Davide Gadioli, Gianluca Palermo, Andrea Bartolini, Luca Benini, Jan Martinovic, Martin Palkovic, Katerina Slaninova, Joao Bispo, Joao M. P. Cardoso, Rui Abreu, Pedro Pinto, Carlo Cavazzoni, Nico Sanna, Andrea R. Beccari, Radim Cmar, Erven Rohou

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Tags: Compilers, Computer science, DSL, Energy-efficient computing, OpenCL

August 1, 2016 by hgpu

Drug Drug Interaction Extraction from Biomedical Literature Using Syntax Convolutional Neural Network

Zhehuan Zhao, Zhihao Yang, Ling Luo, Hongfei Lin, Jian Wang

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Tags: Bioinformatics, Biology, CUDA, Deep learning, Neural networks, NLP, nVidia, Package, Python, Tesla K20, Text mining

August 1, 2016 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

Inside VOLT: Designing an Open-Source GPU Compiler (Tool)

SciDef: Automated Definition Extraction from Scientific Literature

SciDef: Automating Definition Extraction from Academic Literature with Large Language Models

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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