TY - GEN
T1 - Fault tolerant design for low power hierarchical search motion estimation algorithms
AU - Dhoot, Charvi
AU - Mooney, Vincent J.
AU - Chowdhury, Shubhajit Roy
AU - Chau, Lap Pui
PY - 2011/10
Y1 - 2011/10
N2 - Highly scaled CMOS devices are predicted to show probabilistic behavior due to process variations or the presence of noise sources such as thermal noise. Past research dealing with characterizing CMOS devices with probabilistic behavior has shown that computing via these devices, termed probabilistic computing, can help realize highly efficient circuits in terms of energy consumption. In this paper, we explore low power motion estimation, specifically low power hierarchical search algorithms for motion estimation, in the context of probabilistic computing. With the fault tolerant algorithm design (MC-TSS) proposed in this paper, we show that energy savings that can be realized with probabilistic computing increase to 70% versus 57% with the conventional algorithm (TSS), with minor impact on the quality of motion estimation. Furthermore, a 1.8 dB improvement in PSNR under the same energy savings of 70% for both algorithms is shown establishing the superior resilience of the proposed algorithm to probabilistic computing over the conventional algorithm.
AB - Highly scaled CMOS devices are predicted to show probabilistic behavior due to process variations or the presence of noise sources such as thermal noise. Past research dealing with characterizing CMOS devices with probabilistic behavior has shown that computing via these devices, termed probabilistic computing, can help realize highly efficient circuits in terms of energy consumption. In this paper, we explore low power motion estimation, specifically low power hierarchical search algorithms for motion estimation, in the context of probabilistic computing. With the fault tolerant algorithm design (MC-TSS) proposed in this paper, we show that energy savings that can be realized with probabilistic computing increase to 70% versus 57% with the conventional algorithm (TSS), with minor impact on the quality of motion estimation. Furthermore, a 1.8 dB improvement in PSNR under the same energy savings of 70% for both algorithms is shown establishing the superior resilience of the proposed algorithm to probabilistic computing over the conventional algorithm.
KW - fault-tolerant design
KW - low power design
KW - motion estimation
KW - PCMOS architecture
KW - probabilistic computing
UR - https://www.scopus.com/pages/publications/83755163069
U2 - 10.1109/VLSISoC.2011.6081649
DO - 10.1109/VLSISoC.2011.6081649
M3 - Conference article published in proceeding or book
AN - SCOPUS:83755163069
SN - 9781457701719
T3 - 2011 IEEE/IFIP 19th International Conference on VLSI and System-on-Chip, VLSI-SoC 2011
SP - 266
EP - 271
BT - 2011 IEEE/IFIP 19th International Conference on VLSI and System-on-Chip, VLSI-SoC 2011
T2 - 2011 IEEE/IFIP 19th International Conference on VLSI and System-on-Chip, VLSI-SoC 2011
Y2 - 3 October 2011 through 5 October 2011
ER -
