Scope and Topics

The ACM/SPEC International Conference on Performance Engineering (ICPE) is the leading international forum for presenting and discussing novel ideas, innovations, trends, and experiences in the field of performance engineering.

Performance, energy efficiency, and reliability are becoming central to the acceptance and sustainability of modern computing systems. Digitalization brings computing technology closer to people and manages most aspects of their life. In turn, human interaction increasingly shapes the behavior of computing systems. As a result, our systems become more complex and, therefore, more difficult to engineer and understand. We need to be able to manage this complexity so that our systems remain reliable, trustable, and performant.

ICPE brings together researchers and practitioners to report on open problems, state-of-the-art solutions, and in-progress research in performance engineering of software and systems - targeting performance and associated quality attributes such as efficiency and reliability in all phases of the computing system lifecycle, from specification and development to run time and maintenance.

ICPE deals with performance and associated quality attributes across any and all application domains. Here is a list of examples:

    cyber-physical domain, IoT, industrial internet
    communication networks, wireless and mobile
    peer-to-peer environments, ad-hoc networks
    SOA, microservices, web-based environments
    big data systems, stream and graph processing
    data-intensive systems, data analytics and data science
    machine learning and artificial intelligence
    HPC systems, cloud, edge, grid and fog
    multimedia systems and applications
    autonomous, resilient, adaptive and agentic systems and applications

Types of Submissions

ICPE caters to a wide range of submission types with eight distinct submission tracks:

    Research track for novel research on the conference topics
    Industry track for research involving industry
    Journal-first track for contributions from recent journal publications
    Artifact track for sharing software and data artifacts
    Emerging research track for discussing preliminary or vision contributions
    Poster and demo track for short interactive contributions
    Tutorials track for presentations by leading scientists and practitioners
    Workshops track for specific aspects of performance engineering
    Data challenge track for addressing the challenges presented by a performance dataset

Topics of interest

Topics of interest include, but are not limited to:

Measurement and Empirical Evaluation

    data collection techniques, simulation, measurement, instrumentation, profiling
    controlled experiment design, data driven experiments, diagnostics
    data management and interchange, tool interoperability
    statistical analysis, exploration, visualization, visual data mining
    measuring and evaluating
        performance and related attributes such as energy efficiency, stability or resource usage
        dependability and related attributes such as security, resiliency or confidentiality
        algorithmic attributes such as learning efficiency or solution quality

Modeling

    approaches and metrics for describing performance and related quality attributes
    modeling languages and formalisms, modeling methods and tools
    explanatory and predictive models, online models
    model learning and extraction techniques
    model validation and calibration
    workload characterization

Design and Development Processes

    requirements engineering, agile and experiment driven techniques, devops
    performance-oriented design, software architectures, performance patterns and antipatterns
    performance testing, root cause and bottleneck identification
    humans in the loop, ethical concerns

Managing Systems at Runtime

    adaptive systems, monitoring, autotuning, elasticity and autoscaling, power management
    virtualization and consolidation, resource scheduling, capacity management
    anomaly detection, service level (definition and monitoring)

Platform-Related Optimizations

    parallel programming, multi-core and many-core systems
    compiler optimizations, managed languages and runtime optimization
    performance and efficiency of hardware accelerators and novel memory systems

Benchmarking

    design and standardization process
    benchmark suites, investigative benchmarks
    benchmark synthesis, benchmark workload generation
    benchmarking energy efficiency, resilience, stability, security and related quality metrics