Towards More Efficient Logic Blocks by Exploiting Biconditional Expansion

Nowadays, <em>Field Programmable Gate Arrays</em> (FPGA) exploit <em>Look-Up Tables</em> (LUTs) to generate logic functions. A <em>K</em>-input LUT can implement any Boolean functions with <em>K</em> inputs. Thanks to this flexibility, LUTs remained conceptually unchanged in FPGAs, only the number of inputs increased in time. Unfortunately, the flexibility does not come for free and LUTs have non-negligible costs in both circuit-level performances (large number of memories, area or delay penalties) and logic-level capabilities (limited fan-out). Here, we propose an FPGA fabric based on two novel logic blocks. First, we introduce a new LUT design showing reduced power consumption with no sacrifice in the logic flexibility. Then, we present a block suited to arithmetic functions but preserving enough versatility to implement general logic functions. The two blocks are supported by a recently introduced logic representation called <em>Biconditional Binary Decision Diagrams</em> (BBDDs). Using architectural-level benchmarking, we showed that an FPGA architecture exploiting the novel blocks performs significantly better than current state-of-the-art FPGA architectures at 40nm technological node over a large set of test circuits. While reducing the power consumption of MCNC big20 benchmarks by 29%, the proposed architecture is able to efficiently implement arithmetic circuits as compared to its traditional LUT-based FPGA counterpart. For instance, a 256-bit adder can be realized with a 43% gain in area×delay product. While considering large general and arithmetic logic benchmarks, we observe, on average, 4%, 3% and 10% improvements in area, delay and power respectively.


Published in:
Proceedings of the 23rd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2015), 262-262
Presented at:
23rd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2015), Monterey, California, USA, February 22-24, 2015
Year:
2015
ISBN:
978-1-4503-3315-3
Laboratories:




 Record created 2015-01-07, last modified 2018-01-28

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