Recent Trends in Parallel Computing

Computer/IT ISSN 2393-8749 3 issues a year Hybrid open access

Submit a manuscript Search this journal Editorial board (7)

About the journal

Recent Trends in Parallel Computing is a peer-reviewed hybrid open-access journal launched in 2014. Parallel computing is a form of computation in which many calculations can be done at the same time and it works on the principle that large problems can often be divided into smaller ones, which are then solved in parallel. Specialized parallel computer architectures are sometimes used aboard traditional processors, to quicken specific tasks this increases the speed of execution of the task.

View full aims and scope →

Journal metrics

Counted from this archive, not supplied by anyone.

  • 37Articles published
  • 5Published in 2026
  • 93Authors
  • 2Open access

Journal information

Title
Recent Trends in Parallel Computing
Issues per year
3 issues
ISSN
2393-8749
Publisher
STM Journals
DOI
10.37591/RTPC
Starting year
2024
Subject
Computer/IT
Publication format
Hybrid open access
Language
English
Type
Peer-reviewed journal (refereed)

Indexed in

Editorial board

  • Editor-in-Chief

    Prof. Pinaki Mitra

    Computer Science and Engineering, Indian Institute of Technology, Guwahati, India

All 7 board members →

Latest articles

  • Published Subscription Review Article

    A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora

    Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …

    Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article

  • Published Subscription Review Article

    Adaptive Task Scheduling And Resource Optimization Using Ai Middleware

    Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …

    Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article

  • Published Subscription Review Article

    Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures

    Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …

    Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article

  • Published Subscription Review Article

    Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications

    Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …

    Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article

  • Published Subscription Review Article

    Application of Proportional-Share with Punishment Principle for Resource Sharing in Parallel Computing Applications

    Abstract: Efficient resource sharing is a cornerstone of high-performance parallel computing. While proportional-share scheduling has long been a foundational approach for distributing resources according to predefined weights, its effectiveness can be compromised by tasks that over-consume their allocated share, leading to system-wide performance degradation and unfairness. This review article investigates the application of the “Proportional-Share with Punishment” (PSWP) principle, a hybrid scheduling paradigm designed to address this challenge. PSWP integrates the …

    Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article

  • Published Subscription Review Article

    A Meta-Analysis of the Role of Serverless Computing Models in Modern e-Healthcare Systems

    Abstract: The integration of serverless computing models in e-healthcare systems represents a paradigm shift in healthcare technology infrastructure. This meta-analysis examines the role, benefits, and challenges of serverless architectures in modern healthcare applications, focusing on studies published between 2019 and 2025. Serverless computing offers unprecedented scalability, cost-efficiency, and operational flexibility, making it particularly suited for healthcare applications handling variable workloads such as medical imaging processing, real-time patient monitoring, and electronic health …

    Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 49–58 Read article

  • Published Subscription Original Research

    Enhancing Security in Unified Software Architecture for Smart Computing IoT Devices via Mobile App Authentication Using Quantum-Based Encryption

    Abstract: Security remains a critical concern in the landscape of smart computing for IoT devices, necessitating robust measures to safeguard sensitive data and user privacy. In this context, the utilization of quantum-based encryption presents a promising avenue to enhance security in unified software architecture. This study proposes a model aimed at fortifying the security of IoT devices by integrating mobile app authentication with quantum-based encryption techniques. The model leverages Quantum Key …

    Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 41–48 Read article

  • Published Subscription Review Article

    NutriHeart with Chatbot

    Abstract: Heart disease stands as one of the world's principal reasons for human deaths since it causes major preventable fatalities each year. Healthcare institutions currently explore machine learning (ML) integration for establishing new approaches toward predicting, and acting ahead of healthcare developments. NutriHeart presents an AI-based platform that accomplishes cardiovascular risk detection early and extends heart wellness by delivering customized nutritional and lifestyle recommendations. Using Support Vector Machines (SVM) along with …

    Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 22–34 Read article

All 37 articles in this journal →

Ahead of print

Accepted and online before they are assigned to an issue.

  • Published Ahead of print Open access Article

    Comparison of Various Load Balancing Algorithms in Cloud Computing

    Abstract: The components associated with distributed computing are customers, datacenter and appropriated server. One of the principal issuesin distributed computing isload adjusting. Adjusting the heap intends to circulate the outstanding task at hand among a few hubs uniformly so no single hub will be over- burden. Burden can be of any kind that is it very well may be CPU load, memory limit or system load. Right now, introduced a design …

    Published in Recent Trends in Parallel Computing Read article

  • Published Ahead of print Open access Article

    A Study of Virtual Machines Environment in Cloud Computing

    Abstract: The Cloud computing is most widely used technological concept which gives the efficient result in concern to availability and utilizing of resources, processing and management of the data on servers. These capabilities make cloud computing to decorate the programs of it. The concept of virtualization of cloud computing is main feature of this technology which provide a platform to many business application data, academic IT tools and industry to explore …

    Published in Recent Trends in Parallel Computing Read article

Archive on its own page →

Volume 13 (2026) 5 articles

Volume 12 (2025) 15 articles

Volume 11 (2024) 15 articles

Support