INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS

Scope & Guideline

Exploring Cutting-Edge Developments in Computing

Introduction

Explore the comprehensive scope of INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN1094-3420
PublisherSAGE PUBLICATIONS LTD
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 1987 to 2024
AbbreviationINT J HIGH PERFORM C / Int. J. High Perform. Comput. Appl.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND

Aims and Scopes

The INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS focuses on advancing the field of high-performance computing (HPC) through innovative applications, methodologies, and performance optimizations. Its core research areas encompass diverse computational techniques and frameworks aimed at enhancing computational efficiency and effectiveness across various scientific domains.
  1. High-Performance Algorithms and Libraries:
    Research on the development and optimization of algorithms and libraries that enhance computational performance, including linear algebra, iterative solvers, and specialized libraries for GPUs and CPUs.
  2. Exascale Computing Solutions:
    Focus on methodologies and tools that facilitate exascale computing, addressing challenges such as performance scalability, resource management, and application portability.
  3. Parallel Computing Techniques:
    Exploration of parallel computing paradigms, including MPI, OpenMP, and hybrid programming models that leverage multi-core and many-core architectures for improved performance.
  4. Data-Driven Performance Optimization:
    Utilization of machine learning and data analysis techniques to optimize performance in high-performance computing environments, including workload characterization and scheduling.
  5. Scientific Application Development:
    Development of computational frameworks and methodologies for specific scientific applications, such as climate modeling, fluid dynamics, and molecular dynamics, emphasizing performance and accuracy.
  6. Interdisciplinary Approaches:
    Integration of HPC with other fields such as AI, data science, and materials science to address complex computational problems and enhance the capability of scientific simulations.
Recent publications in the INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS highlight several emerging themes that are gaining traction and relevance in high-performance computing research.
  1. Exascale Computing Challenges:
    An increasing number of studies are addressing the unique challenges posed by exascale computing, including resource management, performance optimization, and application scalability, reflecting the community's focus on future computing architectures.
  2. Machine Learning and AI Integration:
    The integration of machine learning and artificial intelligence into HPC applications is a growing trend, with research exploring how these technologies can enhance performance, automate workflows, and improve decision-making processes.
  3. Heterogeneous Computing Environments:
    A significant emphasis on heterogeneous computing, combining CPUs, GPUs, and specialized hardware, is evident, as researchers seek to optimize performance across diverse architectures.
  4. Advanced Visualization Techniques:
    Emerging studies focus on advanced visualization techniques for large-scale data generated by HPC applications, enhancing the ability to interpret complex results effectively.
  5. Sustainable and Energy-Efficient Computing:
    Research is increasingly directed towards sustainability and energy efficiency in HPC, exploring methods to reduce the carbon footprint and improve the energy performance of high-performance computing systems.

Declining or Waning

Over the years, certain themes within the INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS have shown a decline in prominence, indicating a shift in research focus and priorities within the field.
  1. Traditional CPU-based Computation:
    There has been a noticeable decrease in research focused solely on traditional CPU-based computing methods, as the shift towards GPU and heterogeneous computing becomes more pronounced.
  2. Basic Numerical Methods:
    Research centered on fundamental numerical methods without significant enhancements or optimizations is becoming less common, as the community increasingly emphasizes advanced, application-specific solutions.
  3. Legacy Software Systems:
    The study of legacy software systems and their optimization has waned, with a greater emphasis now placed on developing new architectures and programming models tailored for modern HPC environments.
  4. Non-Exascale Applications:
    Investigations into non-exascale applications are less frequently published, reflecting a trend towards tackling the challenges presented by exascale computing and its associated complexities.
  5. Generalized Performance Metrics:
    Research that focuses on generalized performance metrics without context-specific applications is declining, as more studies emphasize targeted performance improvements for specific applications or architectures.

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