本数据集旨在为分子动力学程序在多FPGA卡上的高效并行实现与优化提供一套全面、可量化的特征基准。采用Vivado HLS 2022.2及Vitis工具链，通过系统化探索经典MD算法在多硬件实现上的并行（核心变量包括粒子受力通信与FPGA协同），构建了开源的结构化数据集。其核心内容涵盖实现配置参数、程序结构特征及仿真验证数据，时空精度覆盖内核执行周期与单元至全芯片资源映射。所有数据均通过自动化脚本从

国家基础学科公共科学数据中心160

scale_model_data.xlsx

性能评估

性能预测

This file contains the performance results for the scale-models as well as the miss rate curves for all benchmarks such that the target-system performance predictions can be reproduced without havi

DataCite Commons2023-11-28 更新50

Crossfit Athletes

CrossFit

性能预测

Can you predict how well a Crossfit Athlete performs?

kaggle2023-03-02 更新190

Techmaster event log

过程挖掘

性能预测

Techmaster log for the replication of experiments described in Context-Aware Process Performance Indicator Prediction in IEEE Access 2020.

NIAID Data Ecosystem100