Papers on hgpu.org (.txt-file)
Importance of Explicit Vectorization for CPU and GPU Software Performance

Importance Point Projection for GPU-based Final Gathering

Importance sampling algorithms for first passage time probabilities in the infinite server queue

Importance Sampling of Realistic Light Sources

Importance-driven compositing window management

Importance-Driven Isosurface Decimation for Visualization of Large Simulation Data Based on OpenCL

Importance-Driven Particle Techniques for Flow Visualization

Impostors and pseudo-instancing for GPU crowd rendering

Impostors, Pseudo-instancing and Image Maps for GPU Crowd Rendering

Improved automated lattice perturbation theory in background field gauge

Improved Distance Weighted GPU-based 3D Ultrasound Reconstruction Methods

Improved FCM algorithm for Clustering on Web Usage Mining

Improved Finite Difference Schemes for a 3-D Viscothermal Wave Equation on a GPU

Improved GPU Co-processor Sorting Algorithm with Barrier Synchronization

Improved Implementation of Simulation for Membrane Computing on the Graphic Processing Unit

Improved Integral Histogram Algorithm for Big Sized Images in CUDA Environment

Improved Lossless Image Compression Model Using Coefficient Based Discrete Wavelet Transform

Improved OpenCL-based Implementation of Social Field Pedestrian Model

Improved Performance of CaFE and IRIS Model Fitting Using CUDA

Improved Poisson Matting for a Real Time Tele-presence System Using GPU
Improved Programming of GPU Architectures through Automated Data Allocation and Loop Restructuring
Improved Real-Time Stereo on Commodity Graphics Hardware

Improved Row-Grouped CSR Format for Storing of Sparse Matrices on GPU

Improved Sequential & Parallel Designs and Implementations of the Eight Direction Prewitt Edge Detection

Improvement of the fused CUDA kernels performance prediction

Improvement Study of EEMD Decomposition Efficiency Based on CUDA Architecture

Improvements to Physically Based Cloth Simulation

Improving 3D Lattice Boltzmann Method stencil with asynchronous transfers on many-core processors

Improving accuracy for matrix multiplications on GPUs
Improving Atmospheric Model Performance on a Multi-Core Cluster System

Improving Automatic Parallel Training via Balanced Memory Workload Optimization

Improving Cache Locality for GPU-based Volume Rendering

Improving Cache Locality for Ray Casting with CUDA

Improving Code Generation via Small Language Model-as-a-judge

Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters

Improving Communication Performance in GPU-Accelerated HPC Clusters

Improving CUDA DNA Analysis Software with Genetic Programming

Improving CUDASW++, a Parallelization of Smith-Waterman for CUDA Enabled Devices

Improving energy and power efficiency using NComputing and approaches for predicting reliability of complex computing systems

Improving Energy Efficiency of Basic Linear Algebra Routines on Heterogeneous Systems with Multiple GPUs

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

Improving GPGPU Concurrency with Elastic Kernels

Improving GPU particle filter with shader model 3.0 for visual tracking

Improving GPU Performance by Regrouping CPU-Memory Data

Improving GPU Performance Prediction with Data Transfer Modeling

Improving GPU Performance through Instruction Redistribution and Diversification

Improving GPU Performance via Large Warps and Two-Level Warp Scheduling

Improving GPU Performance: Reducing Memory Conflicts and Latency

Improving GPU programming models through hardware cache coherence

Improving GPU Robustness by Making Use of Faulty Parts

Improving GPU Simulations of Spiking Neural P Systems

Improving GPU Sparse Matrix-Vector Multiplication for Probabilistic Model Checking

Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search

Improving HPC Code Generation Capability of LLMs via Online Reinforcement Learning with Real-Machine Benchmark Rewards

Improving Hybrid OpenCL Performance by High Speed Networks
Improving Locality of Unstructured Mesh Algorithms on GPUs

Improving Loop Parallelization by a Combination of Static and Dynamic Analyses in HLS

Improving many flavor QCD simulations using multiple GPUs

Improving Numerical Accuracy for Non-Negative Matrix Multiplication on GPUs using Recursive Algorithms

Improving numerical reproducibility and stability in large-scale numerical simulations on GPUs

Improving OpenACC compatibility within accULL

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

Improving OpenCL Programmability with the Heterogeneous Programming Library

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Improving Performance and Energy Consumption of Runtime Schedulers for Dense Linear Algebra

Improving Performance and Energy Efficiency of GPUs through Locality Analysis

Improving Performance and Energy Efficiency of Heterogeneous Systems with rCUDA

Improving performance for emergent environments parameter tuning and simulation in games using GPU
Improving Performance of Hardware Accelerators by Optimizing Data Movement: A Bioinformatics Case Study

Improving Performance of Iterative Applications through Interleaved Execution of Approximated CUDA Kernels

Improving Performance of Matrix Multiplication and FFT on GPU

Improving Performance of OpenCL on CPUs

Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Improving performance portability for GPU-specific OpenCL kernels on multi-core/many-core CPUs by analysis-based transformations

Improving Performance Portability in OpenCL Programs

Improving processing time for visual measurements of displacements of IPMC actuators using CUDA
Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Improving Resource Efficiency in Virtualized Datacenters

Improving Resource Utilization in Heterogeneous CPU-GPU Systems

Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations

Improving SIMD efficiency for parallel Monte Carlo light transport on the GPU

Improving SIMT Efficiency of Global Rendering Algorithms with Architectural Support for Dynamic Micro-Kernels

Improving SMT performance: an application of genetic algorithms to configure resizable caches
Improving Student Learning in Computer Science Courses by Using Virtual OpenCL Laboratory

Improving Synchronization and Data Access in Parallel Programming Models

Improving tasks throughput on accelerators using OpenCL command concurrency

Improving the Efficiency of GPU Clusters

Improving the Efficiency of OpenCL Kernels through Pipes

Improving the GPU space of computation under triangular domain problems

Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs

Improving the Neural GPU Architecture for Algorithm Learning

Improving the Performance of a Ray Tracing Algorithm Using a GPU
Improving the Performance of CA-GMRES on Multicores with Multiple GPUs

Improving the Performance of Fully Connected Neural Networks by Out-of-Place Matrix Transpose

Improving the Performance of Hyperspectral Image and Signal Processing Algorithms Using Parallel, Distributed and Specialized Hardware-Based Systems

Improving the Performance of OpenCL-based FPGA Accelerator for Convolutional Neural Network

Improving the performance of PIR Protocol in Outsourced Databases
Improving the performance of spatial raster analysis in GIS using GPU
Improving the Performance of the Contextual Spaces Re-Ranking Algorithm on Heterogeneous Systems

Improving the Performance of the Linear Systems Solvers Using CUDA

Titles: 100
open PDFs: 90
packages: 9
