โ Scribed by Martin Pohl
No coin nor oath required. For personal study only.
I present global design principles for the implementation of High Energy Physics data analysis code on sequential and parallel processors with mixed shared and local memory. Potential parallelism in the structure of High Energy Physics tasks is identified with granularity varying from a few times 108 instructions all the way down to a few times i0~instructions. It follows the hierarchical structure of detector and data acquisition systems. To take advantage of thisyet preserving the necessary portability of the code -I propose a computational model with purely data driven concurrency in Single Program Multiple Data (SPMD) mode. The Task granularity is defined by varying the granularity of the central data structure manipulated. Concurrent processes coordinate themselves asynchroneously using simple lock constructs on parts of the data structure. Load balancing among processes occurs naturally. The scheme allows to map the internal layout of the data structure closely onto the layout of local and shared memory in a parallel architecture. It thus allows to optimize the application with respect to synchronization as well as data transport overheads. I present a coarse top level design for a portable implementation of this scheme on sequential machines, multiprocessor mainframes (e.g. IBM 3090), tightly coupled multiprocessors (e.g. RP-3) and loosely coupled processor arrays (e.g. LCAP, Emulating Processor Farms).
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