Efficient Runtime Management of Reconfigurable Hardware Resources

Abstract

Runtime reconfigurable systems built upon devices with partial reconfiguration can provide reduction in overall hardware area, power efficiency, and economic cost in addition to the performance improvements due to better customization. However, the users of such systems have to be able to afford some additional costs compared to hardwired application specific circuits. More precisely reconfigurable devices have higher power consumption, occupy larger silicon area and operate at lower speeds. Higher power consumption requires additional packaging cost, shortens chip lifetimes, requires expensive cooling systems, decreases system reliability and prohibits battery operation. The less efficient usage of silicon real estate is usually compensated by the runtime hardware reconfiguration and functional units relocation. The available configuration data paths, however, have limited bandwidth that introduces overheads that may eclipse the dynamic reconfiguration benefits. In this dissertation, we address three major problems related to hardware resources runtime management: efficient online hardware task scheduling and placement, power consumption reduction and reconfiguration overhead minimization. Since hardware tasks are allocated and deallocated dynamically at runtime, the reconfigurable fabric can suffer of fragmentation. This can lead to the undesirable situation that tasks cannot be allocated even if there would be sufficient free area available. As a result, the overall system performance is degraded. Therefore, efficient hardware management of resources is very important. To manage hardware resources efficiently, we propose novel online hardware task scheduling and placement algorithms on partially reconfigurable devices with higher quality and faster execution compared to related proposals. To cope with the high power consumption in field programmable devices, we propose a novel logic element with lower power consumption compared to current approaches. To reduce runtime overhead, we augment the FPGA configuration circuit architecture and allow faster reconfiguration and relocation compared to current reconfigurable devices.