Abstract. Partial reconfiguration (PR) of FPGAs can be used to dynamically extend and adapt the functionality of computing systems, swapping in and out HW tasks. To coordinate the on-demand task execution, we propose and implement a run time system manager for scheduling software (SW) tasks on available processor(s) and hardware (HW) tasks on any number of reconfigurable regions of a partially reconfigurable FPGA. Fed with the initial partitioning of the application into tasks, the corresponding task graph, and the available task mappings, the RTSM considers the runtime status of each task and region, e.g. busy, idle, scheduled for reconfiguration/execution etc., to execute tasks. Our RTSM supports task reuse and configuration prefetching to minimize reconfigurations, task movement among regions to efficiently manage the FPGA area, and RR reservation for future reconfiguration and execution. We validate its correctness using our RTSM to execute an image processing application on a ZedBoard platform. We also evaluate its features within a simulation framework, and find that despite the technology limitations, our approach can give promising results in terms of quality of scheduling. IntroductionReconfiguration can dynamically adapt the functionality of hardware systems by swapping in and out HW tasks. To select the proper resource for loading and triggering HW task reconfiguration and execution in partially reconfigurable systems with FPGAs, efficient and flexible runtime system support is needed [6]. In this paper we propose and implement a Run-Time System Manager (RTSM) incorporating efficient scheduling mechanisms that balance effectively the execution of HW and SW tasks and the use of physical resources. We aim to execute as fast as possible a given application, without exhausting the physical resources. Our motivation during the development of RTSM was to find ways to overcome the strict technology restrictions imposed by the Xilinx PR flow [8]:  Static partitioning of the reconfigurable surface in reconfigurable regions (RR).

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Abstract-To handle the stringent performance requirements of future exascale-class applications, High Performance Computing (HPC) systems need ultra-efficient heterogeneous compute nodes. To reduce power and increase performance, such compute nodes will require hardware accelerators with a high degree of specialization. Ideally, dynamic reconfiguration will be an intrinsic feature, so that specific HPC application features can be optimally accelerated, even if they regularly change over time.In the EXTRA project, we create a new and flexible exploration platform for developing reconfigurable architectures, design tools and HPC applications with run-time reconfiguration built-in as a core fundamental feature instead of an add-on. EXTRA covers the entire stack from architecture up to the application, focusing on the fundamental building blocks for run-time reconfigurable exascale HPC systems: new chip architectures with very low reconfiguration overhead, new tools that truly take reconfiguration as a central design concept, and applications that are tuned to maximally benefit from the proposed run-time reconfiguration techniques. Ultimately, this open platform will improve Europe's competitive advantage and leadership in the field.

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Abstract-To handle the stringent performance requirements of future exascale-class applications, High Performance Computing (HPC) systems need ultra-efficient heterogeneous compute nodes. To reduce power and increase performance, such compute nodes will require hardware accelerators with a high degree of specialization. Ideally, dynamic reconfiguration will be an intrinsic feature, so that specific HPC application features can be optimally accelerated, even if they regularly change over time.In the EXTRA project, we create a new and flexible exploration platform for developing reconfigurable architectures, design tools and HPC applications with run-time reconfiguration built-in as a core fundamental feature instead of an add-on. EXTRA covers the entire stack from architecture up to the application, focusing on the fundamental building blocks for run-time reconfigurable exascale HPC systems: new chip architectures with very low reconfiguration overhead, new tools that truly take reconfiguration as a central design concept, and applications that are tuned to maximally benefit from the proposed run-time reconfiguration techniques. Ultimately, this open platform will improve Europe's competitive advantage and leadership in the field.