This paper describes several system-level interconnection strategies for a coarse-grained reconfigurable fabric designed for low-energy hardware acceleration. A small, representative sub-graph for signal and image processing applications is used to predict the success of mapping larger applications onto the fabric device with these different interconnection strategies, which include 32:1, 8:1, 5:1, 4:1, 3553:1 (3:1, 5:1, 5:1, 3:1) and 355:1 (3:1, 5:1, 5:1) cardinalities. Three mapping techniques are presented and used to complete mappings onto several of these fabric instances including a mixed integer linear programming technique, a constraint programming approach, and a greedy heuristic. We present results for area (in number of required rows), power, delay, and energy as well as run times for mapping a set of signal and image processing benchmarks onto each of these interconnects. Our results indicate that the 5:1 interconnect provides the best overall results and does not require any additional hardware resources than the baseline 4:1 technique. When compared with other implementation strategies, the reconfigurable fabric energy consumption, using 5:1-based interconnect, is within 5-10X of a direct ASIC implementation, is 10X better than an Virtex II Pro FPGA and is 100X better than an Intel XScale processor.