Heterogeneous systems-on-chip (SoCs) are highly favorable computing platforms due to their superior performance and energy efficiency potential compared to homogeneous architectures. They can be further tailored to a specific domain of applications by incorporating processing elements (PEs) that accelerate frequently used kernels in these applications. However, this potential is contingent upon optimizing the SoC for the target domain and utilizing its resources effectively at runtime. To this end, system-level design -including scheduling, power-thermal management algorithms and design space exploration studies -plays a crucial role. This paper presents a system-level domain-specific SoC simulation (DS3) framework to address this need. DS3 enables both design space exploration and dynamic resource management for power-performance optimization of domain applications. We showcase DS3 using six real-world applications from wireless communications and radar processing domain. DS3, as well as the reference applications, is shared as open-source software to stimulate research in this area.

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Domain-specific systems-on-chip, a class of heterogeneous many-core systems, are recognized as a key approach to narrow down the performance and energy-efficiency gap between custom hardware accelerators and programmable processors. Reaching the full potential of these architectures depends critically on optimally scheduling the applications to available resources at runtime. Existing optimization-based techniques cannot achieve this objective at runtime due to the combinatorial nature of the task scheduling problem. As the main theoretical contribution, this paper poses scheduling as a classification problem and proposes a hierarchical imitation learning (IL)-based scheduler that learns from an Oracle to maximize the performance of multiple domainspecific applications. Extensive evaluations with six streaming applications from wireless communications and radar domains show that the proposed IL-based scheduler approximates an offline Oracle policy with more than 99% accuracy for performance-and energy-based optimization objectives. Furthermore, it achieves almost identical performance to the Oracle with a low runtime overhead and successfully adapts to new applications, many-core system configurations, and runtime variations in application characteristics.

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Process technology-driven performance and energy efficiency improvements have slowed down as we approach physical design limits. General-purpose manycore architectures attempt to circumvent this challenge, but they have a significant performance and energy-efficient gap compared to special-purpose solutions. Domain-specific architectures (DSAs), an instance of heterogeneous architectures, efficiently combine general-purpose cores and specialized hardware accelerators to boost energy efficiency and provide programming flexibility. Indeed, the hardware, software, and systems aspects in DSAs are highly tailored to maximize the energy efficiency of applications in a target domain. As DSAs and their conceptualization advance rapidly, there is a strong need to understand the research problems that need immediate attention. This paper discusses the primary research directions in the design and runtime management of DSAs. Then, it surveys some promising approaches and highlights the outstanding research needs.