Heterogeneity is emerging 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 different node architectures are interconnected with potentially heterogeneous networks, to the micro level, where deeper memory hierarchies and different accelerator architectures are increasingly common, the impact of heterogeneity on all computing tasks is rapidly increasing. Traditional parallel algorithms, programming environments and tools designed for older homogeneous multiprocessors will at best achieve a small fraction of the efficiency and potential performance that we should expect from parallel computing in tomorrow's highly diverse and mixed environments. New ideas, innovative algorithms, and specialised programming environments and tools are needed to efficiently exploit these new and diverse parallel architectures. The workshop aims to provide a forum for researchers working on algorithms, programming languages, tools, and theoretical models aimed at efficiently solving problems on heterogeneous platforms.

RISC-V is an open standard Instruction Set Architecture (ISA) which enables the open development of CPUs and a shared common software ecosystem. There are already over 15 billion RISC-V cores, which is accelerating rapidly. Nonetheless, for all the successes that RISC-V has faced, it is yet to become popular in HPC. Recent advances however, such as the vectorisation standard and high performance  RISC-V-based CPUs and accelerators, mean that this technology is becoming a more realistic proposition for our workloads. This workshop aims to connect those currently involved in RISC-V with the wider HPC community. We look to bring together RISC-V experts with scientific software developers, vendors, and supercomputing center operators to explore the advantages, challenges, and opportunities that RISC-V can bring to HPC. This is being organised by the RISC-V HPC SIG, which we aim to expand with a range of HPC expertise and viewpoints, enabling interested attendees to then participate in this field beyond the workshop and help drive one of the most exciting open-source technological activities of our time.

The “Compute Continuum” paradigm promises to manage the heterogeneity and dynamism of widespread computing resources, aiming to simplify the execution of distributed applications improving data locality, performance, availability, adaptability, energy management as well as other non-functional features. This is made possible by overcoming resource fragmentation and segregation in tiers, enabling applications to be seamlessly executed and relocated along a continuum of resources spanning from the edge to the cloud. Besides consolidated vertical and horizontal scaling patterns, this paradigm also offers more detailed adaptation actions that strictly depend on the specific infrastructure components (e.g., to reduce energy consumption, or to exploit specific hardware such as GPUs and FPGAs). This enables the enhancement of latency-sensitive applications, the reduction of network bandwidth consumption, the improvement of privacy protection, and the development of novel services aimed at improving living, health, safety, and mobility. All of this should be achievable by application developers without having to worry about how and where the developed components will be executed. Therefore, to unleash the true potential offered by the Compute Continuum, proactive, autonomous, and infrastructure-aware management is desirable, if not mandatory, calling for novel interdisciplinary approaches that exploit optimization theory, control theory, machine learning, and artificial intelligence methods.