PapersFlow Research Brief
Distributed and Parallel Computing Systems
Research Guide
What is Distributed and Parallel Computing Systems?
Distributed and Parallel Computing Systems are computing infrastructures that coordinate multiple processors or computers to perform tasks concurrently, focusing on resource management, task scheduling, workflow management, computational grids, service-oriented science, data grids, high-performance computing, and virtual organizations.
This field encompasses 193,867 works with no specified 5-year growth rate. Key areas include grid computing, distributed systems, and high-performance computing. Systems enable scalable resource sharing across large-scale networks as defined in foundational papers.
Topic Hierarchy
Research Sub-Topics
Grid Resource Management and Allocation
Researchers design middleware for dynamic resource discovery, reservation, and co-allocation across heterogeneous grid nodes. Studies address QoS guarantees, brokerage protocols, and integration with economic models for fair sharing.
Distributed Task Scheduling Algorithms
This area develops heuristics and metaheuristics for scheduling independent and dependent tasks in grid environments, optimizing makespan, load balance, and fault tolerance. Research evaluates performance on real workloads and simulators like GridSim.
Scientific Workflow Management in Grids
Scientists engineer workflow engines like Pegasus and Taverna for orchestrating complex, data-intensive pipelines across grids. Focus includes provenance tracking, adaptive execution, and interoperability with cloud hybrids.
Data Grids and Replica Management
Research on systems like Storage Resource Broker and Replica Location Service handles petabyte-scale data distribution, consistency, and prefetching in grids. Topics cover semantic replication and data movement optimization.
Virtual Organizations in Computational Grids
This sub-topic explores authorization frameworks, policy enforcement, and community middleware for dynamic VOs in grids. Studies prototype single sign-on and attribute-based access control for multi-institutional collaborations.
Why It Matters
Distributed and parallel computing systems support large-scale resource sharing for applications like distributed supercomputing, data-intensive computing, and real-time instrumentation, as outlined in "The Grid 2: Blueprint for a New Computing Infrastructure" (1998) by Ian Foster and Carl Kesselman, which details sections on computational grids and programming tools. "The Anatomy of the Grid: Enabling Scalable Virtual Organizations" (2001) by Ian Foster, Carl Kesselman, and Steven Tuecke describes grid computing's focus on virtual organizations, enabling coordination of distributed resources for high-performance tasks with 6560 citations. These systems underpin bioinformatics tools like Clustal W and X version 2.0 (2007) by Larkin et al., which uses parallel alignment for sequence analysis with 28604 citations, and Geneious Basic (2012) by Kearse et al. for organizing biological data across computational resources with 19977 citations.
Reading Guide
Where to Start
"The Anatomy of the Grid: Enabling Scalable Virtual Organizations" (2001) by Ian Foster, Carl Kesselman, and Steven Tuecke, as it provides a clear definition and review of grid computing fundamentals distinguishing it from conventional systems.
Key Papers Explained
"The Grid 2: Blueprint for a New Computing Infrastructure" (1998) by Ian Foster and Carl Kesselman lays the infrastructure blueprint with sections on computational grids and tools, which "The Anatomy of the Grid: Enabling Scalable Virtual Organizations" (2001) by Ian Foster, Carl Kesselman, and Steven Tuecke builds upon by detailing scalable virtual organizations. "Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment" (1973) by C. L. Liu and J. W. Layland provides foundational scheduling theory applicable to grid task management. "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility" (2008) by Rajkumar Buyya et al. extends grid concepts to cloud platforms.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Recent preprints target scalable load-balancing in "TD-Orch: Scalable Load-Balancing for Distributed Systems with Applications to Graph Processing" for supercomputers and datacenters. IEEE Transactions on Parallel and Distributed Systems publishes on models of computation and data-intensive algorithms with a 6.0 impact factor. News highlights Photonic Inc. raising $180M CAD for distributed quantum computing and IBM-Cisco collaboration on networked quantum systems by the early 2030s.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | Lecture Notes in Computer Science 1205 | 1999 | Industrial Robot the i... | 38.7K | ✕ |
| 2 | Clustal W and Clustal X version 2.0 | 2007 | Bioinformatics | 28.6K | ✓ |
| 3 | Geneious Basic: An integrated and extendable desktop software ... | 2012 | Bioinformatics | 20.0K | ✓ |
| 4 | Scheduling Algorithms for Multiprogramming in a Hard-Real-Time... | 1973 | Journal of the ACM | 8.3K | ✓ |
| 5 | The art of case study research | 1996 | Library & Information ... | 8.3K | ✕ |
| 6 | The Grid 2: Blueprint for a New Computing Infrastructure | 1998 | — | 7.6K | ✕ |
| 7 | Simulating physics with computers | 1982 | International Journal ... | 7.2K | ✕ |
| 8 | The Anatomy of the Grid: Enabling Scalable Virtual Organizations | 2001 | The International Jour... | 6.6K | ✕ |
| 9 | Julia: A Fresh Approach to Numerical Computing | 2017 | SIAM Review | 5.9K | ✕ |
| 10 | Cloud computing and emerging IT platforms: Vision, hype, and r... | 2008 | Future Generation Comp... | 5.9K | ✕ |
In the News
Photonic Raises $180M CAD to Accelerate Distributed ...
**Photonic Inc.**, a global leader in distributed quantum computing, announced today that it has raised $180M CAD ($130M USD) in the first close of its latest investment round**,**led by **Planet F...
Distributed Computing News
January 29, 2026 ## Top Headlines Scientists Say Quantum Tech Has Reached Its Transistor Moment
2025 Awards and Achievements in Parallel Processing
# 2025 Awards and Achievements in Parallel Processing Published 07/09/2025 Share this on: ## The Role of TCPP in Advancing ## Parallel Processing
Science Highlight: Breakthrough Computing Method Speeds ...
## **Funding:** SciDAC-5 FASTMath Institute.
Parallel Computing Market Size, Trends & Forecast, 2025- ...
- On November 20, 2025, IBM and Cisco announced an intention to collaborate on the groundwork for networked distributed quantum computing, to be realized as soon as the early 2030s. By combining IB...
Code & Tools
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplif...
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplif...
A library for distributed computation. See documentation for more details. ## About A distributed task scheduler for Dask distributed.dask.org ##...
Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make distribu...
Apache Pekko is an open-source framework for building applications that are concurrent, distributed, resilient and elastic. Pekko uses the Actor Mo...
Recent Preprints
Distributed, Parallel, and Cluster Computing
# Distributed, Parallel, and Cluster Computing ## Authors and titles for recent submissions * Fri, 30 Jan 2026 * Thu, 29 Jan 2026 * Wed, 28 Jan 2026 * Tue, 27 Jan 2026 * Mon, 26 Jan 2026 See t...
IEEE Transactions on Parallel and Distributed Systems
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.© Copyright 2025 IEEE - All rights reser...
CSDL Pub Home: Transactions on Parallel and Distributed Systems
_IEEE Transactions on Parallel and Distributed Systems_ publishes the latest research relating to parallel and distributed systems such as models of computation, data-intensive parallel algorithms,...
TD-Orch: Scalable Load-Balancing for Distributed Systems with Applications to Graph Processing
Distributed-memory computer systems, including supercomputers [89], multi-socket NUMAs [63], compute-equipped disaggregated memory [19,51], processing-in-memory [82,100], computational storage [4...
Computer Science > Distributed, Parallel, and Cluster Computing
at a low resource cost. Subjects:|Distributed, Parallel, and Cluster Computing (cs.DC)|
Latest Developments
Recent developments in distributed and parallel computing systems research include upcoming conferences such as IPDPS 2026, PDP 2026, and HPDC 2026, which focus on advancements in AI, high-performance systems, and infrastructure, as well as a special issue in MDPI highlighting the evolution of secure, efficient distributed systems (ipdps.org, pdp2026.org, hpdc.sci.utah.edu, mdpi.com).
Sources
Frequently Asked Questions
What are computational grids?
Computational grids coordinate distributed resources for high-performance applications such as distributed supercomputing and data-intensive computing. "The Grid 2: Blueprint for a New Computing Infrastructure" (1998) by Ian Foster and Carl Kesselman covers applications including real-time widely distributed instrumentation systems. These grids enable scalable virtual organizations as detailed in "The Anatomy of the Grid: Enabling Scalable Virtual Organizations" (2001).
How does task scheduling work in hard real-time environments?
In hard real-time multiprogramming, fixed priority schedulers have an upper bound on processor utilization. "Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment" (1973) by C. L. Liu and J. W. Layland shows optimum schedulers may achieve low utilization due to program characteristics requiring guaranteed service. This approach addresses single-processor scheduling for real-time functions.
What is the role of Julia in numerical computing?
Julia provides a high-performance approach to numerical computing by combining computer science and computational science expertise. "Julia: A Fresh Approach to Numerical Computing" (2017) by Jeff Bezanson, Alan Edelman, Stefan Karpinski, and Viral B. Shah designs it to be easy, fast, and scalable for diverse fields. It challenges traditional laws of numerical computing practices with 5936 citations.
How do grids differ from conventional distributed computing?
Grids focus on large-scale resource sharing, innovative applications, and high-performance orientation beyond conventional distributed systems. "The Anatomy of the Grid: Enabling Scalable Virtual Organizations" (2001) by Ian Foster, Carl Kesselman, and Steven Tuecke reviews grid anatomy for virtual organizations. This enables coordination across wide-area networks.
What applications use distributed computing in bioinformatics?
Bioinformatics tools like Clustal W and X version 2.0 use distributed resources for multiple sequence alignment. The 2007 rewrite by Mark Larkin et al. in C++ supports porting to modern systems including Linux and Macintosh, earning 28604 citations. Geneious Basic (2012) by Kearse et al. organizes and analyzes sequence data on desktop computational frameworks.
Open Research Questions
- ? How can load-balancing be optimized for graph processing in distributed-memory systems like supercomputers and datacenters, as explored in recent preprints?
- ? What scheduling bounds improve utilization in multiprogramming for emerging hard real-time distributed environments?
- ? How do virtual organizations scale resource sharing in data grids amid increasing computational demands?
- ? What algorithms enhance workflow management in service-oriented science on computational grids?
- ? How can photonic technologies integrate with distributed quantum computing infrastructures for high-performance grids?
Recent Trends
Fields like Distributed, Parallel, and Cluster Computing show 77 recent entries as of January 2026.
"TD-Orch: Scalable Load-Balancing for Distributed Systems with Applications to Graph Processing" addresses load-balancing for supercomputers and datacenters.
2025IEEE Transactions on Parallel and Distributed Systems maintains a 6.0 impact factor with over 5,100 peer-reviewed papers.
Photonic Inc. secured $180M CAD funding for distributed quantum computing in January 2026.
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