Symmetry/Asymmetry in Numerical Analysis and Scientific Computing
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 61
Special Issue Editors
Interests: GPU computing; MPI; OpenMP; CUDA; parallel programming
Special Issue Information
Dear Colleagues,
This Special Issue of Symmetry explores the role of symmetry and asymmetry in numerical analysis and parallel computing algorithms, focusing on their impact on performance optimization and computational efficiency. Symmetry is fundamental in balancing loads in GPU and multi-GPU architectures, ensuring efficient resource utilization while minimizing bottlenecks in parallel processing.
Furthermore, maintaining balance and symmetry is critical for optimizing performance in numerical analysis and parallel programming models, such as OpenMP, SYCL, OpenACC, and MPI, as well as their hybrid implementations. Effective load-balancing strategies, guided by considerations regarding symmetry, help distribute workloads evenly across processing units, leading to scalable and high-performance computing solutions. Symmetry helps optimize performance; asymmetry also plays a role, especially in heterogeneous architectures, where different computing resources (e.g., CPUs, GPUs, and accelerators) have varying performance characteristics. Addressing asymmetric workloads in numerical methods and parallel computing is an ongoing research challenge, requiring adaptive scheduling and load-balancing techniques.
This Special Issue invites contributions that analyze theoretical and practical aspects of symmetry in parallel algorithms, explore innovative approaches for handling asymmetry in numerical analysis and heterogeneous computing environments, and propose novel methodologies for improving efficiency in modern high-performance computing (HPC) applications.
Dr. Carlos Couder-Castañeda
Dr. José Carlos Ortiz Alemán
Guest Editors
Manuscript Submission Information
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Keywords
- numerical analysis
- parallel computing
- symmetry in algorithms
- asymmetry in computing
- load balancing
- GPU computing
- multi-GPU systems
- heterogeneous computing
- high-performance computing (HPC)
- OpenMP
- SYCL
- OpenACC
- MPI
- hybrid parallel programming
- performance optimization
- scalability in parallel systems
- task scheduling
- algorithm efficiency
- computational workload distribution
- resource allocation
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