TY - GEN
T1 - High performance radiation transport simulations
T2 - 2012 24th International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012
AU - Baker, C.
AU - Davidson, G.
AU - Evans, T. M.
AU - Hamilton, S.
AU - Jarrell, J.
AU - Joubert, W.
PY - 2012
Y1 - 2012
N2 - In this paper we describe the Denovo code system. Denovo solves the six-dimensional, steady-state, linear Boltzmann transport equation, of central importance to nuclear technology applications such as reactor core analysis (neutronics), radiation shielding, nuclear forensics and radiation detection. The code features multiple spatial differencing schemes, state-of-the-art linear solvers, the Koch-Baker-Alcouffe (KBA) parallel-wavefront sweep algorithm for inverting the transport operator, a new multilevel energy decomposition method scaling to hundreds of thousands of processing cores, and a modern, novel code architecture that supports straightforward integration of new features. In this paper we discuss the performance of Denovo on the 20+ petaflop ORNL GPU-based system, Titan. We describe algorithms and techniques used to exploit the capabilities of Titan's heterogeneous compute node architecture and the challenges of obtaining good parallel performance for this sparse hyperbolic PDE solver containing inherently sequential computations. Numerical results demonstrating Denovo performance on early Titan hardware are presented.
AB - In this paper we describe the Denovo code system. Denovo solves the six-dimensional, steady-state, linear Boltzmann transport equation, of central importance to nuclear technology applications such as reactor core analysis (neutronics), radiation shielding, nuclear forensics and radiation detection. The code features multiple spatial differencing schemes, state-of-the-art linear solvers, the Koch-Baker-Alcouffe (KBA) parallel-wavefront sweep algorithm for inverting the transport operator, a new multilevel energy decomposition method scaling to hundreds of thousands of processing cores, and a modern, novel code architecture that supports straightforward integration of new features. In this paper we discuss the performance of Denovo on the 20+ petaflop ORNL GPU-based system, Titan. We describe algorithms and techniques used to exploit the capabilities of Titan's heterogeneous compute node architecture and the challenges of obtaining good parallel performance for this sparse hyperbolic PDE solver containing inherently sequential computations. Numerical results demonstrating Denovo performance on early Titan hardware are presented.
UR - http://www.scopus.com/inward/record.url?scp=84877693414&partnerID=8YFLogxK
U2 - 10.1109/SC.2012.64
DO - 10.1109/SC.2012.64
M3 - Conference contribution
AN - SCOPUS:84877693414
SN - 9781467308069
T3 - International Conference for High Performance Computing, Networking, Storage and Analysis, SC
BT - 2012 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012
Y2 - 10 November 2012 through 16 November 2012
ER -