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ICPE '20: Companion of the ACM/SPEC International Conference on Performance Engineering
ACM2020 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
ICPE '20: ACM/SPEC International Conference on Performance Engineering Edmonton AB Canada April 25 - 30, 2020
ISBN:
978-1-4503-7109-4
Published:
20 April 2020
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Abstract

Years of planning went into the preparation of ICPE 2020 in Edmonton. There was great excitement in bringing ICPE back to North America after a while and great anticipation for productive interactions between the participants of ICPE and members of the various SPEC working groups. But, alas, the only certain thing about life is its uncertainty. The arrival of the COVID-19 pandemic led to the cancelation of the face-to-face conference in Edmonton. ICPE proceeded with the publication of these proceedings and with the availability of video presentations and slides linked to the conference program in the website. The great program for ICPE 2020 was made possible thanks to the many authors that submitted contributions to the advancement of performance modeling and engineering and many other related topics. We were anticipating great interest in the strong line of keynote speakers. The Canadian-based line up is a coincidence but it would have been a great way to celebrate the contributions from Canadian universities in this area. Gail Murphy from the University of British Columbia planned to share her experiences in increasing the productivity of software development. Sebastian Fishmeister from the University of Waterloo would talk about what they learned from mining traces from the design of embedded software systems. Ahmed Hassan from Queens University intended talk about assessing and testing large-scale software systems.

There is much work that goes into putting together a complex program such as ICPE. Besides the contributing authors and presenters, many volunteering hours were dedicated by chairs, programcommittee members, local organizers, local volunteers, steering-committee members and many others. On behalf of the ICPE community we thank you all for your effort and dedication. We thank for the generous sponsorship from the Standard Performance Evaluation Corporation (SPEC).

Even though ICPE could not go ahead as planned because of the 2020 pandemic, we hope that the availability of video presentations and the publication of these proceedings will lead to productive online interactions between researchers.

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SESSION: The Eighth International Workshop on Load Testing and Benchmarking of Software Systems (LTB'20)
research-article
Migrating a Recommendation System to Cloud Using ML Workflow

Inference is the production stage of machine learning workflow in which a trained model is used to infer or predict with real world data. A recommendation system improves customer experience by displaying most relevant items based on historical behavior ...

SESSION: Workshop on Challenges and Opportunities in Large-Scale Performance (WOSP-C)
research-article
WOSP-C 2020: Workshop on Challenges and Opportunities in Large-Scale Performance: Welcoming Remarks

It is my great pleasure to welcome you to WOSP-C 2020, the Workshop on Challenges and Opportunities in Large Scale Performance. Our theme this year relates to the use of analytics to interpret system performance and resource usage measurements that can ...

research-article
Performance Anomaly and Change Point Detection For Large-Scale System Management

We begin by presenting a short overview of the classical Statistical Process Control based Anomaly Detection techniques and tools including Multivariate Adaptive Statistical Filtering, Statistical Exception Detection System, Exception Value meta-metric ...

research-article
Automated Scalability Assessment in DevOps Environments

In this extended abstract, we provide an outline of the presentation planned for WOSP-C 2020. The goal of the presentation is to provide an overview of the challenges and approaches for automated scalability assessment in the context of DevOps and ...

research-article
Issues Arising in Using Kernel Traces to Make a Performance Model

This report is prompted by some recent experience with building performance models from kernel traces recorded by LTTng, a tracer that is part of Linux, and by observing other researchers who are analyzing performance issues directly from the traces. It ...

research-article
How to Apply Modeling to Compare Options and Select the Appropriate Cloud Platform

Organizations want to take advantage of the flexibility and scalability of Cloud platforms. By migrating to the Cloud, they hope to develop and implement new applications faster with lower cost. Amazon AWS, Microsoft Azure, Google, IBM, Oracle and ...

SESSION: The Third Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf'20)
research-article
Towards Performance Modeling of Speculative Execution for Cloud Applications

Interesting approaches to counteract performance variability within cloud datacenters include sending multiple request clones, either immediately or after a specified waiting time. In this paper we present a performance model of cloud applications that ...

research-article
Migrating from Monolithic to Serverless: A FinTech Case Study

Serverless computing is steadily becoming the implementation paradigm of choice for a variety of applications, from data analytics to web applications, as it addresses the main problems with serverfull and monolithic architecture. In particular, it ...

research-article
Beyond Microbenchmarks: The SPEC-RG Vision for a Comprehensive Serverless Benchmark

Serverless computing services, such as Function-as-a-Service (FaaS), hold the attractive promise of a high level of abstraction and high performance, combined with the minimization of operational logic. Several large ecosystems of serverless platforms, ...

SESSION: POSTERS & EXHIBITS
abstract
Kubernetes: Towards Deployment of Distributed IoT Applications in Fog Computing

Fog computing has been regarded as an ideal platform for distributed and diverse IoT applications. Fog environment consists of a network of fog nodes and IoT applications are composed of containerized microservices communicating with each other. ...

abstract
Acceleration Opportunities in Linear Algebra Applications via Idiom Recognition

General matrix-matrix multiplication (GEMM) is a critical operation in many application domains [1]. It is a central building block of deep learning algorithms, computer graphics operations, and other linear algebra dominated applications. Due to this, ...

abstract
Poster Abstract: Fair and Efficient Dynamic Bandwidth Allocation with OpenFlow

Large-scale not-for-profit Internet Service Providers (ISPs), such as National Research and Education Networks (NRENs) often have significant amounts of underutilized bandwidth because they provision their network capacity for the rare event that all ...

SESSION: Work-in-Progress
research-article
Energy Efficiency Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite

The growth of cloud services leads to more and more data centers that are increasingly larger and consume considerable amounts of power. To increase energy efficiency, both the actual server equipment and the software themselves must become more energy-...

research-article
JBrainy: Micro-benchmarking Java Collections with Interference

Software developers use collection data structures extensively and are often faced with the task of picking which collection to use. Choosing an inappropriate collection can have major negative impact on runtime performance. However, choosing the right ...

SESSION: Tutorials
tutorial
Performance Engineering for Microservices and Serverless Applications: The RADON Approach

Microservices and serverless functions are becoming integral parts of modern cloud-based applications. Tailored performance engineering is needed for assuring that the applications meet their requirements for quality attributes such as timeliness, ...

tutorial
Tutorial on Benchmarking Big Data Analytics Systems

The proliferation of big data technology and faster computing systems led to pervasions of AI based solutions in our life. There is need to understand how to benchmark systems used to build AI based solutions that have a complex pipeline of pre-...

Contributors
  • University of Alberta
  • Karlsruhe Institute of Technology
  • Gran Sasso Science Institute
  • Free University Amsterdam
  1. Companion of the ACM/SPEC International Conference on Performance Engineering

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