Special Issue 19th international workshop on algorithms, models and tools for parallel computing on heterogeneous platforms (HeteroPar'21)

Abstract

Heterogeneity has emerged as one of the most profound and challenging characteristics of today's parallel environments. From the macro level, where networks of distributed computers, composed of diverse node architectures, are interconnected with potentially heterogeneous networks, to the micro level, where deeper memory hierarchies and various accelerator architectures are increasingly common, the impact of heterogeneity on all computing tasks is increasing rapidly. Traditional parallel algorithms, programming environments, and tools, designed for legacy homogeneous multiprocessors, achieve a small fraction of the efficiency and the potential performance that can be obtained in current and future heterogeneous computing platforms. New ideas, innovative algorithms, and specialized programming environments and tools are needed to efficiently use these modern parallel and heterogeneous architectures. The International workshop on algorithms, models and tools for parallel computing on heterogeneous platforms (HeteroPar) is a forum for researchers working on algorithms, programming languages, tools, and theoretical models for efficiently solving complex problems on heterogeneous parallel platforms. HeteroPar 2021 took place (virtually) in Lisbon, Portugal, organized for the 13th time in conjunction with the Euro-Par annual international conference. The format of the workshop included one keynote and 11 technical presentations. The workshop papers represented an interesting mix of topics, addressing the implementation of algorithms and kernels for heterogeneous computing, programming models, data management, runtime and resource management, energy efficiency, cloud computing, and artificial intelligence-based methods oriented towards heterogeneous platforms, as the basis for the next generation exascale computers. The selected papers cover a good spectrum of research topics in the area of heterogeneous computing showing the challenges present on these modern platforms.