https://www.cs.ccu.edu.tw/~pahsiung/publications/papers/DPRS_JSA2010.pdf

Model-based platform-specific co-design methodology for dynamically partially reconfigurable systems with hardware virtualization and preemption

Modern applications running on today's embedded systems have very high requirements. Most often, these requirements have many dimensions: the applications need high performance as well as exibility ...

/pdf/hardware-software-codesign-of-embedded-systems-with-4pn6pohk59.pdf

Hardware/Software Codesign of Embedded Systems with Reconfigurable and Heterogeneous Platforms

Many modern applications exhibit a dynamic and nonstationary behavior, with certain characteristics in one phase of their execution, which change as the application enters new phases, in a manner unpredictable at design-time. In order to meet the demands of such applications, it is important to have adaptive and self-reconfiguring hardware platforms, coupled with intelligent on-line optimization algorithms, that together can adjust to the run-time requirements. Partially dynamically reconfigurable field programmable gate array architectures offer both high performance and flexibility. Despite these potential advantages, the challenges faced by designers trying to set-up a functioning system are still significant, mainly because of the still immature design tools and limited device drivers. We propose a complete framework, based on Xilinx’s commercial design suite, that enables an application designer to leverage the advantages of partial dynamic reconfiguration with minimal effort. Our IP-based architecture, together with the comprehensive application programming interface, can be employed to accelerate an application by dynamically scheduling hardware prefetches. Moreover, a piecewise linear predictor is used to capture correlations and predict the hardware modules that will generate the highest performance improvement. Our evaluation comprises of extensive simulations, as well as a complete implementation of the smallest univalue segment assimilating nucleus image processing application on the ML605 board from Xilinx. The measurements show a significant reduction of the expected execution time compared to previous state-of-the-art prefetching algorithms, with only a minor energy overhead.

A Reconfigurable Framework for Performance Enhancement With Dynamic FPGA Configuration Prefetching

One of the main drawbacks that significantly impacts the performance of dynamically reconfigurable systems (like FPGAs), is their high reconfiguration overhead. Configuration prefetching is one method to reduce this penalty by overlapping FPGA reconfigurations with useful computations. In this paper we propose a speculative approach that schedules prefetches at design time and simultaneously performs HW/SW partitioning, in order to minimize the expected execution time of an application. Our method prefetches and executes in hardware those configurations that provide the highest performance improvement. The algorithm takes into consideration profiling information (such as branch probabilities and execution time distributions), correlated with the application characteristics. Compared to the previous state-of-art, we reduce the reconfiguration penalty with 34% on average, and with up to 59% for particular case studies.

/pdf/minimization-of-average-execution-time-based-on-speculative-ielrbtteud.pdf

Minimization of average execution time based on speculative FPGA configuration prefetch

In most existing works, reconfigurable hardware modules are still managed as conventional hardware devices. Further, the software reconfiguration overhead incurred by loading corresponding device drivers into the kernel of an operating system has been overlooked until now. As a result, the enhancement of system performance and the utilization of reconfigurable hardware modules are still quite limited. This work proposes a virtualizable hardware/software design infrastructure (VDI) for dynamically partially reconfigurable systems. Besides the gate-level hardware virtualization provided by the partial reconfiguration technology, VDI supports the device-level hardware virtualization. In VDI, a reconfigurable hardware module can be virtualized such that it can be accessed efficiently by multiple applications in an interleaving way. A Hot-Plugin Connector (HPC) replaces the conventional device driver, such that it not only assists the device-level hardware virtualization but can also be reused across different hardware modules. To facilitate hardware/software communication and to enhance system scalability, the proposed VDI is realized as a hierarchical design framework. User-designed reconfigurable hardware modules can be easily integrated into VDI, and are then executed as hardware tasks in an operating system for reconfigurable systems (OS4RS). A dynamically partially reconfigurable network security system was designed using VDI, which demonstrated a higher utilization of reconfigurable hardware modules and a reduction by up to 12.83p of the processing time required by using the conventional method in a dynamically partially reconfigurable system.

Virtualizable hardware/software design infrastructure for dynamically partially reconfigurable systems

With the gradually fading distinction between hardware and software, it is now possible to relocate tasks from a microprocessor to reconfigurable logic and vice versa. However, existing hardware-software scheduling can rarely cope with such runtime task relocation. In this work, we propose a new Relocatable Hardware-Software Scheduling (RHSS) method that not only can be applied to dynamically relocatable hardware-software tasks, but also increases the reconfigurable hardware resource utilization, reduces the reconfigurable hardware resource fragmentation with realistic placement methods, and makes best efforts at meeting the real-time constraints of tasks. The feasibility of the proposed relocatable hardware-software scheduling algorithm was proved by applying it to some randomly generated examples and a real dynamically reconfigurable network security system example. Compared to the quadratic time complexity of the state-of-the-art Adaptive Hardware-Software Allocation (AHSA) method, RHSS is linear in time complexity, and improves the reconfigurable hardware utilization by as much as 117.8p. The scheduling and placement time and the memory usage are also drastically reduced by as much as 89.5p and 96.4p, respectively.

Chen-Chi Chiang

Papers

Scheduling and Placement of Hardware/Software Real-Time Relocatable Tasks in Dynamically Partially Reconfigurable Systems