Performance upgrades to the MCNP6 burnup capability for large scale depletion calculations

• Increased computational horsepower identified a noticeable slowdown in MCNP6 burnup calculations using many burnable regions.
• Computational performance strategies strategies addressed include: cross section retreival during transport; and tallying mechanisms specific to burnup.
• A simple pin cell calculation, using the cross section retrieval upgrade, demonstrated a speedup of 1.94.
• A complex full reactor calculation demonstrated a speedup of 70.105 times faster.
• These new performance upgrades were developed and integrated into MCNP6 1.2.

The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. With the merger of MCNPX and MCNP5, MCNP6 combined the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. The new MCNP6 depletion capability was first showcased at the International Congress for Advancements in Nuclear Power Plants (ICAPP) meeting in 2012. At that conference the new capabilities addressed included the combined distributive and shared memory parallel architecture for the burnup capability, improved memory management, physics enhancements, and new predictability as compared to the H.B Robinson Benchmark. At Los Alamos National Laboratory, a special purpose cluster named “tebow,” was constructed such to maximize available RAM per CPU, as well as leveraging swap space with solid state hard drives, to allow larger scale depletion calculations (allowing for significantly more burnable regions than previously examined). As the MCNP6 burnup capability was scaled to larger numbers of burnable regions, a noticeable slowdown was realized. This paper details two specific computational performance strategies for improving calculation speedup: (1) retrieving cross sections during transport; and (2) tallying mechanisms specific to burnup in MCNP. To combat this slowdown new performance upgrades were developed and integrated into MCNP6 1.2.