Distributing and Load Balancing Sparse Fluid Simulations. (12th September 2018)

• Record Type: Journal Article
• Authors: Shah, C.; Hyde, D.; Qu, H.; Levis, P.
• Is Part Of: Computer graphics forum. Volume 37:Number 8(2018)
• Page Start: 35
• Page End: 46
• Publication Date: 2018-09-12
• Subjects: CCS Concepts -- Computing methodologies → Distributed computing methodologies -- Distributed simulation -- Computer graphics; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.13510
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: This paper describes a general algorithm and a system for load balancing sparse fluid simulations. Automatically distributing sparse fluid simulations efficiently is challenging because the computational load varies across the simulation domain and time. A key challenge with load balancing is that optimal decision making requires knowing the fluid distribution across partitions for future time steps, but computing this state for an arbitrary simulation requires running the simulation itself. The key insight of this paper is that it is possible to predict future load by running a speculative low resolution simulation in parallel. We mathematically formulate the problem of load balancing over multiple time steps and present a polynomial time algorithm to compute an approximate solution to it. Our experimental results show that distributing and speculatively load balancing sparse FLIP simulations over 8 nodes speeds them up by 5.3× to 7.9×, and that speculative load balancing generates assignments that perform within 20% of optimal.