Prior work has shown that due to the overhead incurred in enabling reconfigurability, field-programmable gate arrays (FPGAs) require 21× more silicon area, 3× larger delay, and 10× more dynamic power consumption compared with application-specific integrated circuits (ASICs). We have earlier presented a hybrid CMOS/nanotechnology reconfigurable architecture (NATURE). It uses the concept of temporal logic folding and fine-grain (i.e., cycle-level) dynamic reconfiguration to increase logic density by an order of magnitude. Since logic folding reduces area usage significantly, on-chip communications tend to become localized. To take full advantage of this fact, we propose a new architecture, called fine-grain dynamically reconfigurable (FDR), that consists of an array of homogeneous reconfigurable logic elements (LEs). Each LE can be arbitrarily configured into a lookup table (LUT) or interconnect or a combination of both. This significantly enhances the flexibility of allocating hardware resources between LUTs and interconnects based on application needs. The proposed FDR architecture eliminates most of the long-distance and global wires, which occupy most of the area in conventional FPGAs. Fine-grain dynamic reconfiguration is enabled by local embedded static RAM blocks. The experiments show that, on an average, area, delay, and power are improved by 9.14×, 1.11×, and 1.45×, compared with a conventional FPGA architecture that does not use the concept of logic folding. Compared with NATURE with deep logic folding, area, delay, and power are improved by 2.12×, 3.28×, and 1.74×, respectively. Although this does not eliminate the FPGA-ASIC area/delay/power gaps, it makes progress toward bridging these gaps.
|Number of pages||14|
|Journal||IEEE Transactions on Very Large Scale Integration (VLSI) Systems|
|Publication status||Published - Dec 2014|
- Dynamic reconfiguration
- field-programmable gate arrays (FPGAs)
- integrated circuits
- logic folding.
ASJC Scopus subject areas
- Hardware and Architecture
- Electrical and Electronic Engineering