Copertina

HPDR: High-Performance Portable Scientific Data Reduction Framework

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Jieyang, Gong, Qian, Li, Yanliang, Liang, Xin, Wan, Lipeng, Liu, Qing, Podhorszki, Norbert, Klasky, Scott
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

HP-MDR: High-performance and Portable Data Refactoring and Progressive Retrieval with Advanced GPUs
di: Li, Yanliang, et al.
Pubblicazione: (2025)

Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest
di: Wu, Xuan, et al.
Pubblicazione: (2024)

JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows
di: Esaulov, Vladislav, et al.
Pubblicazione: (2025)

Performance Models for a Two-tiered Storage System
di: Sasidharan, Aparna, et al.
Pubblicazione: (2025)

LAPIS: A Performance Portable, High Productivity Compiler Framework
di: Kelley, Brian, et al.
Pubblicazione: (2025)

Portability Efficiency Approach for Calculating Performance Portability
di: Marowka, Ami
Pubblicazione: (2024)

Implementing Multi-GPU Scientific Computing Miniapps Across Performance Portable Frameworks
di: Villalobos, Johansell, et al.
Pubblicazione: (2025)

A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization
di: Wang, Daoce, et al.
Pubblicazione: (2024)

Workflow Mini-Apps: Portable, Scalable, Tunable & Faithful Representations of Scientific Workflows
di: Kilic, Ozgur Ozan, et al.
Pubblicazione: (2024)

Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing
di: Feng, Shengyu, et al.
Pubblicazione: (2025)

Data Management System Analysis for Distributed Computing Workloads
di: Hsu, Kuan-Chieh, et al.
Pubblicazione: (2025)

XaaS Containers: Performance-Portable Representation With Source and IR Containers
di: Copik, Marcin, et al.
Pubblicazione: (2025)

High-Performance Portable GPU Primitives for Arbitrary Types and Operators in Julia
di: Pilliat, Emmanuel
Pubblicazione: (2026)

Towards High-Performance and Portable Molecular Docking on CPUs through Vectorization
di: Accordi, Gianmarco, et al.
Pubblicazione: (2025)

Closer in the Gap: Towards Portable Performance on RISC-V Vector Processors
di: Shi, Ruimin, et al.
Pubblicazione: (2026)

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations
di: Crisci, Luigi, et al.
Pubblicazione: (2024)

Reproducible Cross-border High Performance Computing for Scientific Portals
di: Abarenkov, Kessy, et al.
Pubblicazione: (2022)

A Portable Framework for Accelerating Stencil Computations on Modern Node Architectures
di: Sai, Ryuichi, et al.
Pubblicazione: (2023)

TopoSZp: Lightweight Topology-Aware Error-controlled Compression for Scientific Data
di: Agarwal, Tripti, et al.
Pubblicazione: (2026)

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs
di: Tramm, John, et al.
Pubblicazione: (2024)

Mitigating Artifacts in Pre-quantization Based Scientific Data Compressors with Quantization-aware Interpolation
di: Jiao, Pu, et al.
Pubblicazione: (2026)

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment
di: Vatsavai, Sairam Sri, et al.
Pubblicazione: (2025)

HoSZp: An Efficient Homomorphic Error-bounded Lossy Compressor for Scientific Data
di: Agarwal, Tripti, et al.
Pubblicazione: (2024)

AI Surrogate Model for Distributed Computing Workloads
di: Park, David K., et al.
Pubblicazione: (2024)

STZ: A High Quality and High Speed Streaming Lossy Compression Framework for Scientific Data
di: Wang, Daoce, et al.
Pubblicazione: (2025)

Portable High-Performance Kernel Generation for a Computational Fluid Dynamics Code with DaCe
di: Andersson, Måns I., et al.
Pubblicazione: (2025)

Taking GPU Programming Models to Task for Performance Portability
di: Davis, Joshua H., et al.
Pubblicazione: (2024)

FZModules: A Heterogeneous Computing Framework for Customizable Scientific Data Compression Pipelines
di: Ruiter, Skyler, et al.
Pubblicazione: (2025)

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with SW Sequence Alignment
di: Costanzo, Manuel, et al.
Pubblicazione: (2024)

A Parallel and Highly-Portable HPC Poisson Solver: Preconditioned Bi-CGSTAB with alpaka
di: Pennati, Luca, et al.
Pubblicazione: (2025)

Syndeo: Portable Ray Clusters with Secure Containerization
di: Li, William, et al.
Pubblicazione: (2024)

Enabling High-Throughput Parallel I/O in Particle-in-Cell Monte Carlo Simulations with openPMD and Darshan I/O Monitoring
di: Williams, Jeremy J., et al.
Pubblicazione: (2024)

FUSCO: High-Performance Distributed Data Shuffling via Transformation-Communication Fusion
di: Zhu, Zhuoran, et al.
Pubblicazione: (2025)

LCP: Enhancing Scientific Data Management with Lossy Compression for Particles
di: Zhang, Longtao, et al.
Pubblicazione: (2024)

Efficient and Portable Support for Overdecomposition on Distributed Memory GPGPU Platforms
di: Bhosale, Aditya, et al.
Pubblicazione: (2026)

Understanding Layered Portability from HPC to Cloud in Containerized Environments
di: Medeiros, Daniel, et al.
Pubblicazione: (2024)

Portable, heterogeneous ensemble workflows at scale using libEnsemble
di: Hudson, Stephen, et al.
Pubblicazione: (2024)

ProvDeploy: Provenance-oriented Containerization of High Performance Computing Scientific Workflows
di: Kunstmann, Liliane, et al.
Pubblicazione: (2024)

Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration
di: Wu, Shixun, et al.
Pubblicazione: (2025)

DiOMP-Offloading: Toward Portable Distributed Heterogeneous OpenMP
di: Shan, Baodi, et al.
Pubblicazione: (2025)