High Performance Computing and Computer Architectures
This special issue belongs to the section "Computing and Artificial Intelligence".
Special Issue Information
Dear Colleagues,
Application trends, device technologies, and the architecture of computing systems are driving progress in information technologies. This poses new challenges in the advancement of computer architectures as well as regarding software solutions. Therefore, this Special Issue is intended for the presentation of new ideas and experimental results in the field of high performance computing and computer architectures from design, service, and theory to its practical use.
Areas relevant to high performance computing and computer architectures include, but are not limited to, computation and data-intensive applications, novel concurrent algorithms and applications, large-scale computational science, artificial intelligence, machine learning, deep learning and the processing of voluminous datasets from satellites, scientific experiments, sensor networks, medical instruments, and other sources. Computer architecture necessary to achieve extremely high performance, techniques for resource management in the context of parallel and distributed systems, and energy-aware computing are also topics of interest.
This Special Issue will publish high-quality, original research papers, in the overlapping fields of:
- High-performance computing;
- Parallel and distributed computing;
- Artificial intelligence, machine learning and deep learning;
- Computational and data science;
- Big data applications, algorithms, and systems;
- Ontologies and semantics;
- Cloud/edge/fog computing;
- Green computing;
- Neuromorphic computing;
- Quantum computing.
Keywords
- high perfermance computing
- artificial intelligence, machine learning and deep learning
- processor, memory, and storage systems architecture
- interconnection networks
- instruction, thread and data-level parallelism
- accelerator system design, GPUs, FPGAs, CGRAs power and energy efficient architectures
- application specific, reconfigurable, IoT, mobile and embedded architectures
- architecture modelling and performance evaluation
- machine learning systems, including algorithms/system co-design

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