TY - JOUR
T1 - Efficient Progressive Radiance Estimation Engine Architecture and Implementation for Progressive Photon Mapping
AU - Chiu, Ching Chieh
AU - Van, Lan-Da
AU - Lin, Yu Shu
PY - 2018/8/1
Y1 - 2018/8/1
N2 -
We propose a progressive radiance estimation engine (PREE) hardware architecture to accelerate the processing of the progressive photon mapping with satisfactory graphic quality. The presented PREE architecture consists of four progressive radiance estimation units (PREUs), approximate full task schedule-oriented hit-point update operation controller (AFTSO-HpUOC) and approximate data-independent schedule-oriented radiance evaluation controller (ADISO-REC). The PREUs accelerate the radiance estimation computation by a pipeline technique and share and configure the hardware resource for hit-point update operation and radiance evaluation. Through AFTSO-HpUOC and ADISO-REC, the data can be efficiently dispatched to achieve better parallelism and the data dependence can be alleviated within the four PREUs, respectively. The core area of the proposed PREE architecture implemented in TSMC 90-nm CMOS process is 1.78 mm
2
. According to the post-layout simulation results, the implementation achieves 496.79 million hit-point update operations per second (MHpUO/s) and consumes 184 mW at 125 MHz for Cornell box with three balls.
AB -
We propose a progressive radiance estimation engine (PREE) hardware architecture to accelerate the processing of the progressive photon mapping with satisfactory graphic quality. The presented PREE architecture consists of four progressive radiance estimation units (PREUs), approximate full task schedule-oriented hit-point update operation controller (AFTSO-HpUOC) and approximate data-independent schedule-oriented radiance evaluation controller (ADISO-REC). The PREUs accelerate the radiance estimation computation by a pipeline technique and share and configure the hardware resource for hit-point update operation and radiance evaluation. Through AFTSO-HpUOC and ADISO-REC, the data can be efficiently dispatched to achieve better parallelism and the data dependence can be alleviated within the four PREUs, respectively. The core area of the proposed PREE architecture implemented in TSMC 90-nm CMOS process is 1.78 mm
2
. According to the post-layout simulation results, the implementation achieves 496.79 million hit-point update operations per second (MHpUO/s) and consumes 184 mW at 125 MHz for Cornell box with three balls.
KW - Hardware architecture
KW - progressive photon mapping
KW - progressive radiance estimation
UR - http://www.scopus.com/inward/record.url?scp=85041000018&partnerID=8YFLogxK
U2 - 10.1109/TCSI.2018.2789680
DO - 10.1109/TCSI.2018.2789680
M3 - Article
AN - SCOPUS:85041000018
SN - 1549-8328
VL - 65
SP - 2491
EP - 2502
JO - IEEE Transactions on Circuits and Systems I: Regular Papers
JF - IEEE Transactions on Circuits and Systems I: Regular Papers
IS - 8
ER -