Parallel Programming in the Era of Heterogeneous Computing: Recent Developments and Challenging Issues

Dear Colleagues,

Heterogeneous parallel computing is gaining increasing acceptance as the best solution to simultaneously target different non-functional constraints like power consumption and energy efficiency (excluding performance). However, as the complexity of such computing systems increases, performance limitations due to slow memory access; workload balancing; synchronization; and communication between multi-cores, many-cores, and heterogeneous cores are expected to get worse, making it hard for developers to fully exploit the theoretically available computing power. Compute- and data-intensive tasks can only benefit from hardware's full potential if both processor and architecture characteristics are taken into account at all stages—from the early algorithmic design, via appropriate programming models, to the final implementation. This Special Issue’s objectives include but are not limited to novel programming models and frameworks, or extensions of existing programming models, to ease offloading and parallelization of computation to multi- and many-cores; multi- and many-core applications for emerging scientific computing applications; novel architectural concepts to boost software execution and to overcome scalability issues of current heterogeneous parallel systems; many-core HW/SW design for machine/deep learning processing and applications; software engineering, code optimization, and code generation strategies for parallel systems with heterogeneous processors; multi- and manycore-aware approaches for large-scale parallel simulations in both implementation and algorithm design, including scalability studies, application parallelization use cases, benchmarking, and benchmark suites; and hardware-aware, compute-, and memory-intensive simulations of real-world problems in computational science and engineering.

Dr. Nicola Bombieri
Guest Editor

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