Boosting Performance Optimization with Interactive Data Movement Visualization
Philipp Schaad, Tal Ben-Nun, Torsten Hoefler
摘要
Optimizing application performance in today's hardware architecture landscape is an important, but increasingly complex task, often requiring detailed performance analyses. In particular, data movement and reuse play a crucial role in optimization and are often hard to improve without detailed program inspection. Performance visualizations can assist in the diagnosis of performance problems, but generally rely on data gathered through lengthy program executions. In this paper, we present a performance visualization geared towards analyzing data movement and reuse to inform impactful optimization decisions, without requiring program execution. We propose an approach that combines static dataflow analysis with parameterized program simulations to analyze both global data movement and fine-grained data access and reuse behavior, and visualize insights in-situ on the program representation. Case studies analyzing and optimizing real-world applications demonstrate our tool's effectiveness in guiding optimization decisions and making the performance tuning process more interactive.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper1
相关 Paper
- Sigma: Compiling Einstein Summations to Locality-Aware DataflowTian Zhao, Alexander Rucker, Kunle OlukotunASPLOS 2023 · 被引用 3 次
- C.A.T.S.: Memory and Control Flow Tracing for Whole-Program Performance AnalysisPhilipp Schaad, Tal Ben-Nun, Torsten HoeflerSC 2025 · 被引用 1 次
- TD-NUCA: Runtime Driven Management of NUCA Caches in Task Dataflow Programming ModelsPaul Caheny, Lluc Alvarez, Marc Casas, Miquel MoretóSC 2022 · 被引用 4 次
- Dynamic Detection of Inefficient Data Mapping Patterns in Heterogeneous OpenMP ApplicationsLuke Marzen, Junhyung Shim, Ali JannesariPPoPP 2026
- Classifying Memory Access Patterns for PrefetchingGrant Ayers, Heiner Litz, Christos Kozyrakis, Parthasarathy RanganathanASPLOS 2020 · 被引用 83 次
