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- research-articleSeptember 2023
Murphy: Performance Diagnosis of Distributed Cloud Applications
ACM SIGCOMM '23: Proceedings of the ACM SIGCOMM 2023 ConferenceSeptember 2023, Pages 438–451https://doi.org/10.1145/3603269.3604877Modern cloud-based applications have complex inter-dependencies on both distributed application components as well as network infrastructure, making it difficult to reason about their performance. As a result, a rich body of work seeks to automate ...
- research-articleJune 2022
Doppler: understanding serverless query execution
BiDEDE '22: Proceedings of the International Workshop on Big Data in Emergent Distributed EnvironmentsJune 2022, Article No.: 2, Pages 1–4https://doi.org/10.1145/3530050.3532919Analyzing and understanding query execution dynamics in distributed cloud-based databases is difficult and requires laborious system designs. Serverless query execution, with its massive amount of small, short-lived, and stateless query workers, is even ...
- short-paperMay 2020
Sentinel: Understanding Data Systems
SIGMOD '20: Proceedings of the 2020 ACM SIGMOD International Conference on Management of DataJune 2020, Pages 2729–2732https://doi.org/10.1145/3318464.3384691The complexity of modern data systems and applications greatly increases the challenge in understanding system behaviour and diagnosing performance problems. When these problems arise, system administrators are left with the difficult task of remedying ...
- extended-abstractJune 2018
Hound: Causal Learning for Datacenter-scale Straggler Diagnosis
SIGMETRICS '18: Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer SystemsJune 2018, Pages 59–61https://doi.org/10.1145/3219617.3219641Stragglers are exceptionally slow tasks within a job that delay its completion. Stragglers, which are uncommon within a single job, are pervasive in datacenters with many jobs. We present Hound, a statistical machine learning framework that infers the ...
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ACM SIGMETRICS Performance Evaluation Review: Volume 46 Issue 1, June 2018 - research-articleApril 2018
Hound: Causal Learning for Datacenter-scale Straggler Diagnosis
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), Volume 2, Issue 1Article No.: 17, Pages 1–36https://doi.org/10.1145/3179420Stragglers are exceptionally slow tasks within a job that delay its completion. Stragglers, which are uncommon within a single job, are pervasive in datacenters with many jobs. A large body of research has focused on mitigating datacenter stragglers, but ...
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- research-articleMay 2017
Performance diagnosis for inefficient loops
ICSE '17: Proceedings of the 39th International Conference on Software EngineeringMay 2017, Pages 370–380https://doi.org/10.1109/ICSE.2017.41Writing efficient software is difficult. Design and implementation defects can cause severe performance degradation. Unfortunately, existing performance diagnosis techniques like profilers are still preliminary. They can locate code regions that consume ...
- research-articleJune 2016
DBSherlock: A Performance Diagnostic Tool for Transactional Databases
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1599–1614https://doi.org/10.1145/2882903.2915218Running an online transaction processing (OLTP) system is one of the most daunting tasks required of database administrators (DBAs). As businesses rely on OLTP databases to support their mission-critical and real-time applications, poor database ...
- research-articleMarch 2016
A Resource Contention Analysis Framework for Diagnosis of Application Performance Anomalies in Consolidated Cloud Environments
ICPE '16: Proceedings of the 7th ACM/SPEC on International Conference on Performance EngineeringMarch 2016, Pages 173–184https://doi.org/10.1145/2851553.2851554Cloud services have made large contributions to the agile developments and rapid revisions of various applications. However, the performance of these applications is still one of the largest concerns for developers. Although it has created many ...
- research-articleOctober 2014
Statistical debugging for real-world performance problems
OOPSLA '14: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & ApplicationsOctober 2014, Pages 561–578https://doi.org/10.1145/2660193.2660234Design and implementation defects that lead to inefficient computation widely exist in software. These defects are difficult to avoid and discover. They lead to severe performance degradation and energy waste during production runs, and are becoming ...
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ACM SIGPLAN Notices: Volume 49 Issue 10, October 2014 - posterAugust 2014
Locating throughput bottlenecks in home networks
SIGCOMM '14: Proceedings of the 2014 ACM conference on SIGCOMMAugust 2014, Pages 351–352https://doi.org/10.1145/2619239.2631440We present a demonstration of WTF (Where's The Fault?), a system that localizes performance problems in home and access networks. We implement WTF as custom firmware that runs in an off-the-shelf home router. WTF uses timing and buffering information ...
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ACM SIGCOMM Computer Communication Review: Volume 44 Issue 4, October 2014 - research-articleJune 2013
Toward Fine-Grained, Unsupervised, Scalable Performance Diagnosis for Production Cloud Computing Systems
IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 24, Issue 6June 2013, Pages 1245–1255https://doi.org/10.1109/TPDS.2013.21Performance diagnosis is labor intensive in production cloud computing systems. Such systems typically face many real-world challenges, which the existing diagnosis techniques for such distributed systems cannot effectively solve. An efficient, ...
- research-articleApril 2013
vPerfGuard: an automated model-driven framework for application performance diagnosis in consolidated cloud environments
ICPE '13: Proceedings of the 4th ACM/SPEC International Conference on Performance EngineeringApril 2013, Pages 271–282https://doi.org/10.1145/2479871.2479909Many business customers hesitate to move all their applications to the cloud due to performance concerns. White-box diagnosis relies on human expert experience or performance troubleshooting "cookbooks" to find potential performance bottlenecks. Despite ...
- demonstrationNovember 2010
HI-C: diagnosing object churn in framework-based applications
FSE '10: Proceedings of the eighteenth ACM SIGSOFT international symposium on Foundations of software engineeringNovember 2010, Pages 379–380https://doi.org/10.1145/1882291.1882358In prior work we have developed an escape analysis to help developers identify sources of object churn (i.e., excessive use of temporaries) in large framework-based applications. We have developed Hi-C, an Eclipse plug-in that allows users to visualize, ...
- articleJune 2009
Performance Measurement in Simulation-Based Training
Simulation and Gaming (SIMG), Volume 40, Issue 3June 2009, Pages 328–376https://doi.org/10.1177/1046878108326734Simulation-based training (SBT) is a methodology for providing systematic and structured learning experiences. The effectinvess of this methodology is dependent on the quality of performance measurement practices in place. Performance measurement during ...
- research-articleJune 2008
Rule-based automatic software performance diagnosis and improvement
WOSP '08: Proceedings of the 7th international workshop on Software and performanceJune 2008, Pages 1–12https://doi.org/10.1145/1383559.1383561Performance of a software system is the result of many interacting factors. This paper describes a rule-based framework to identify root causes of performance limits, to untangle the effects of the system configuration (such as the allocation of ...
- articleAugust 2007
Knowledge engineering for automatic parallel performance diagnosis: Research Articles
Concurrency and Computation: Practice & Experience (CCOMP), Volume 19, Issue 11August 2007, Pages 1497–1515Scientific parallel programs often undergo significant performance tuning before meeting their performance expectation. Performance tuning naturally involves a diagnostic process—locating performance bugs that make a program inefficient and explaining ...
- ArticleSeptember 2006
Model-Based relative performance diagnosis of wavefront parallel computations
HPCC'06: Proceedings of the Second international conference on High Performance Computing and CommunicationsSeptember 2006, Pages 200–209https://doi.org/10.1007/11847366_21Parallel performance diagnosis can be improved with the use of performance knowledge about parallel computation models. The Hercule diagnosis system applies model-based methods to automate performance diagnosis processes and explain performance problems ...
- ArticleAugust 2006
Model-based performance diagnosis of master-worker parallel computations
Euro-Par'06: Proceedings of the 12th international conference on Parallel ProcessingAugust 2006, Pages 35–46https://doi.org/10.1007/11823285_5Parallel performance tuning naturally involves a diagnosis process to locate and explain sources of program inefficiency. Proposed is an approach that exploits parallel computation patterns (models) for diagnosis discovery. Knowledge of performance ...
- ArticleMarch 2006
On-line automated performance diagnosis on thousands of processes
PPoPP '06: Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programmingMarch 2006, Pages 69–80https://doi.org/10.1145/1122971.1122984Performance analysis tools are critical for the effective use of large parallel computing resources, but existing tools have failed to address three problems that limit their scalability: (1) management and processing of the volume of performance data ...
- ArticleApril 1995
Capturing and automating performance diagnosis: the Poirot approach
IPPS '95: Proceedings of the 9th International Symposium on Parallel ProcessingApril 1995, Pages 606–613Performance diagnosis, the process of finding and explaining performance problems, is an important part of parallel programming. Effective performance diagnosis requires that the programmer plan an appropriate method, and manage the experiments required ...