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Works (11)
Updated: April 10th, 2024 05:01
2024 article
EASYVIEW: Bringing Performance Profiles into Integrated Development Environments
2024 IEEE/ACM INTERNATIONAL SYMPOSIUM ON CODE GENERATION AND OPTIMIZATION, CGO, pp. 386–398.
author keywords: Profiling; Software optimization; Performance measurement; Visualization; Tools.
arxiv.org (repository)
Source: Web Of Science
Added: April 8, 2024
2023 article
DJXPerf: Identifying Memory Inefficiencies via Object-Centric Profiling for Java
PROCEEDINGS OF THE 21ST ACM/IEEE INTERNATIONAL SYMPOSIUM ON CODE GENERATION AND OPTIMIZATION, CGO 2023, pp. 81–94.
author keywords: Java; profiling; performance optimization; PMU
TL;DR:
DJXPerf is presented, a lightweight, object-centric memory profiler for Java, which associates memory-hierarchy performance metrics (e.g., cache/TLB misses) with Java objects and presents Java object allocation contexts combined with their usage contexts and presents them ordered by the poor locality behaviors.
(via Semantic Scholar)
Source: Web Of Science
Added: November 20, 2023
2023 article
DroidPerf: Profiling Memory Objects on Android Devices
PROCEEDINGS OF THE 29TH ANNUAL INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING, MOBICOM 2023, pp. 75–89.
author keywords: Profiling; memory inefficiencies; performance; Android
TL;DR:
DroidPerf is developed, a lightweight, object-centric memory profiler for ART, which associates memory inefficiencies with objects created and used in Android apps and is able to guide locality optimization on memory layouts, access patterns, and allocation patterns.
(via Semantic Scholar)
Source: Web Of Science
Added: September 18, 2023
2022 article
Graph Neural Networks Based Memory Inefficiency Detection Using Selective Sampling
SC22: INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS.
author keywords: graph neural network; program embedding; memory inefficiency detection; sampling
TL;DR:
This work presents a novel learning-aided system, namely Puffin, to identify three kinds of unnecessary memory operations including dead stores, silent loads and silent stores, by applying gated graph neural networks onto fused static and dynamic program semantics with respect to relative positional embedding.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(OpenAlex)
Source: Web Of Science
Added: June 12, 2023
2022 article
OJXPerf: Featherlight Object Replica Detection for Java Programs
2022 ACM/IEEE 44TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2022), pp. 1558–1570.
TL;DR:
OJXPerf, a lightweight sampling-based profiler, which probabilistically identifies identical objects with code-level attribution can assist developers in refactoring code to eliminate object bloat, and favor reuse of existing object(s).
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Source: Web Of Science
Added: August 29, 2022
2022 article
VALUEEXPERT: Exploring Value Patterns in GPU-Accelerated Applications
ASPLOS '22: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS, pp. 171–185.
author keywords: GPUs; GPU profilers; Profiling Tools; Value Analysis; Value Patterns
TL;DR:
ValueExpert is able to identify previously unknown performance issues and provide suggestions for nontrivial performance improvements with typically less than five lines of code changes, and verify the authors' optimizations with application developers and upstream fixes to their repositories.
(via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 10, 2022
2021 article
Toward Efficient Interactions between Python and Native Libraries
PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), pp. 1117–1128.
author keywords: Python; profiling; PMU; debug register
TL;DR:
PieProf, a lightweight profiler, is developed to pinpoint interaction inefficiencies in Python applications and associate inefficiences with high-level Python code to provide a holistic view, and optimization of 17 realworld applications is guided.
(via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: March 7, 2022
2020 article
DRCCTPROF: A Fine-Grained Call Path Profiler for ARM-Based Clusters
PROCEEDINGS OF SC20: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS (SC20).
author keywords: Fine-grained analysis; ARM; performance analysis; debugging; high-performance computing
TL;DR:
The unique ability of DRCCTPROF is to obtain full calling context at any and every machine instruction that executes, which provides more detailed diagnostic feedback for performance optimization and correctness tools.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(OpenAlex)
Source: Web Of Science
Added: August 16, 2021
2020 article
GVPRoF: A Value Profiler for GPU-Based Clusters
PROCEEDINGS OF SC20: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS (SC20).
Contributors: K. Zhou *, Y. Hao n , J. Mellor-Crummey *, X. Meng * & n
author keywords: High performance computing; Performance analysis; Parallel programming; Supercomputers
TL;DR:
The design and implementation of GVPROF is described, the first value profiler that pinpoints value-related inefficiencies in applications running on NVIDIA GPU-based clusters, which provides useful information to guide code optimization.
(via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 23, 2021
2020 article
SCALANA: Automating Scaling Loss Detection with Graph Analysis
PROCEEDINGS OF SC20: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS (SC20).
author keywords: Performance Analysis; Scalability Bottleneck; Root-Cause Defection; Static Analysis
TL;DR:
A novel approach, called backtracking root cause detection, which can automatically and efficiently detect the root cause of scaling loss and achieve up to 11.11parcent performance improvement by fixing the root causes detected by SCALANA on 2,048 processes.
(via Semantic Scholar)
Source: Web Of Science
Added: August 16, 2021
2020 article
ZeroSpy: Exploring Software Inefficiency with Redundant Zeros
PROCEEDINGS OF SC20: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS (SC20).
author keywords: Redundant Zero; Software Inefficiency; Performance Profiling and Optimization
TL;DR:
This paper proposes ZeroSpy - a fine-grained profiler to identify redundant zeros caused by both inappropriate use of data structures and useless computation and provides intuitive optimization guidance by revealing the locations where the redundantZeros happen in source lines and calling contexts.
(via Semantic Scholar)
Source: Web Of Science
Added: August 16, 2021
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