A Modern Blast Solver Strategy and Its Urban Application


  1. Ripley, R.C.
  2. Zhang, F.
  3. Cloney, C.T.
  4. McClennan, S.
  5. McCormick, N.
Corporate Authors
Defence Research and Development Canada, Suffield Research Centre, Ralston AB (CAN)
The nature of simulating blast effects from explosives and loads in real urban environments requires a CFD-based approach solved on highly discretized 3D domains. First-principles hydrocodes and CFD codes have traditionally been adapted for high-performance computing in distributed environments. The current trend in modern hardware involves many-core architectures, such as multi-processor multi-core CPU and multiple graphics processing units (GPU), often configured together on individual compute nodes. Thus, a next-generation CFD blast code has been developed to employ hybrid GPU/CPU shared-memory computing, which makes optimal use of heterogeneous compute cores in either a workstation or server, and is also scalable to modern parallel clusters. The goal of this modern blast solver is a 50 times speedup using GPU acceleration as compared with its predecessor – e.g., the Chinook code – running on one core of a standard CPU. This up-to-date development necessitated novel solution strategies, including: hybrid shared/distributed memory structure, CFD code optimization for many-core general-purpose GPU, and concurrent CPU/GPU task parallelization. A compact storage technique based on Cartesian meshes combines a zonal meshing strategy, adaptive mesh refinement (AMR), and dynamic Eulerian remapping to ensure maximum resolution of blast effects. The fundamental solver calculation time is 8 – 14 times faster than Chinook’s unstructured mesh CFD solver, and the novel mesh stra
Report Number
DRDC-RDDC-2016-P044 — External Literature
Date of publication
02 Jun 2016
Number of Pages
Electronic Document(PDF)

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