ACM Transactions on Parallel Computing

Aims & Scope

Parallel computing is no longer a niche research field but an essential ingredient in all aspects of computer science.

ACM Transactions on Parallel Computing (TOPC) is a forum for novel and innovative work on all aspects of parallel computing, including foundational and theoretical aspects, systems, languages, architectures, tools, and applications.

It addresses all classes of parallel-processing platforms including concurrent, multithreaded, multicore, accelerated, multiprocessor, clusters, and supercomputers.

TOPC spans the range from foundational research in parallel computing to principles extracted from experimental investigations.

Submissions should describe novel solutions to important challenges in exploiting parallelism.

Solutions should be generic enough to be used beyond the specific application area in which the problem arose.

Papers describing experiences should indicate how they illustrate general principles; papers about parallel computing foundations should indicate how they relate to practice.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.2
2024	0.90

Journal Rank

Year	Value
2024	13388

Journal Citation Indicator

Year	Value
2024	94

SJR (SCImago Journal Rank)

Year	Value
2024	0.418

Quartile

Year	Value
2024	Q3

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Gunrock

  Citation: 103

  Authors: Yangzihao, Yuechao, Andrew, Yuduo, Carl, Leyuan, Muhammad, Chenshan, Weitang, Andy T., John D.

• PowerLyra

  Citation: 103

  Authors: Rong, Jiaxin, Yanzhe, Binyu, Haibing, Haibo

• A Recursive Algebraic Coloring Technique for Hardware-efficient Symmetric Sparse Matrix-vector Multiplication

  Citation: 88

  Authors: Christie, Achim, Alan R., Holger, Georg, Olaf, Jonas, Gerhard

• Remote Memory Access Programming in MPI-3

  Citation: 62

  Authors: Torsten, James, Rajeev, Brian, Pavan, William, Keith

• Fast Greedy Algorithms in MapReduce and Streaming

  Citation: 60

  Authors: Ravi, Benjamin, Sergei, Andrea

• Multigrid for Matrix-Free High-Order Finite Element Computations on Graphics Processors

  Citation: 58

  Authors: Martin, Karl

• Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

  Citation: 54

  Authors: Laxman, Guy E., Julian

• High-Performance and Scalable GPU Graph Traversal

  Citation: 54

  Authors: Duane, Michael, Andrew

• Near-Optimal Scheduling Mechanisms for Deadline-Sensitive Jobs in Large Computing Clusters

  Citation: 49

  Authors: Navendu, Ishai, Joseph (Seffi), Jonathan

• Optimizing I/O Performance of HPC Applications with Autotuning

  Citation: 45

  Authors: Babak, Surendra, Marc

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