Logo des Repositoriums

Auflistung nach Autor:in "Rosales, Eduardo"

1 - 2 von 2
  • Konferenzbeitrag
    Analysis and Optimization of Task Granularity on the Java Virtual Machine
    (Software Engineering 2020, 2020) Rosà, Andrea; Rosales, Eduardo; Binder, Walter
    Our article published in ACM Transactions on Programming Languages and Systems (TOPLAS) (which extends our work published in the proceedings of the 2018 IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2018))presents a new methodology to accurately and efficiently collect the granularity of each executed task. Task granularity, i.e., the amount of work performed by parallel tasks, is a key performance attribute of parallel applications. On the one hand, fine-grained tasksmay introduce considerable parallelization overheads. On the other hand, coarse-grained tasks may not fully utilize the available CPU cores, leading to missed parallelization opportunities. We implement our methodology in tgp, a novel task-granularity profiler that collects carefully selected metrics from the whole system stack with low overhead, and helps developers locate performance and scalability problems. We analyze task granularity in the DaCapo, ScalaBench, and Spark Perf benchmark suites, revealing inefficiencies related to fine-grained and coarse-grained tasks in several applications We demonstrate that the collected task-granularity profiles are actionable by optimizing task granularity in several applications, achieving speedups up to a factor of 5.9x. tgp is available open-source at https://github.com/fithos/tgp/
  • ConferencePaper
    Automated Large-scale Multi-language Dynamic Program Analysis in the Wild
    (Software Engineering 2021, 2021) Villazón, Alex; Sun, Haiyang; Rosà, Andrea; Rosales, Eduardo; Bonetta, Daniele; Defilippis, Isabella; Oporto, Sergio; Binder, Walter
    Our paper published in the proceedings of the 33rd European Conference on Object-Oriented Programming (ECOOP 2019) proposes NAB, a novel framework to execute custom dynamic analysis on open-source software hosted in public repositories. The publication is complemented by an accepted artifact. Analyzing today’s large code repositories has become an important research area for understanding and improving different aspects of modern software systems. Despite the presence of a large body of work on mining code repositories through static analysis, studies applying dynamic analysis to open-source projects are scarce and of limited scale. Nonetheless, being able to apply dynamic analysis to the projects hosted in public code repositories is fundamental for large-scale studies on the runtime behavior of applications, which can greatly benefit the programming-language and software-engineering communities. NAB is fully automatic, language-agnostic, and scalable. We describe NAB’s key features and architecture. We also present three case studies on more than 56K Node.js, Java, and Scala projects, enabling us to 1) understand how developers use JavaScript Promises, 2) identify bad coding practices in JavaScript applications, and 3) locate task-parallel Java and Scala workloads suitable for inclusion in a domain-specific benchmark suite. A preliminary version of NAB is available at http://dag.inf.usi.ch/software/nab/