Irregular Scientific Applications Research Articles

Coordinating Computation and I/O in Massively Parallel Sequence Search

With the explosive growth of genomic information, the searching of sequence databases has emerged as one of the most computation and data-intensive scientific applications. Our previous studies suggested that parallel genomic sequence-search possesses highly irregular computation and I/O patterns. Effectively addressing these runtime irregularities is thus the key to designing scalable sequence-search tools on massively parallel computers. While the computation scheduling for irregular scientific applications and the optimization of noncontiguous file accesses have been well-studied independently, little attention has been paid to the interplay between the two. In this paper, we systematically investigate the computation and I/O scheduling for data-intensive, irregular scientific applications within the context of genomic sequence search. Our study reveals that the lack of coordination between computation scheduling and I/O optimization could result in severe performance issues. We then propose an integrated scheduling approach that effectively improves sequence-search throughput by gracefully coordinating the dynamic load balancing of computation and high-performance noncontiguous I/O.

Irregular Coarse‐Grain Data Parallelism under LPARX

LPARX is a software development tool for implementing dynamic, irregular scientific applications, such as multilevel finite difference and particle methods, on high‐performance multiple instruction multiple data (MIMD) parallel architectures. It supports coarse‐grain data parallelism and gives the application complete control over specifying arbitrary block decompositions. LPARX provides structural abstraction, representing data decompositions as first‐class objects that can be manipulated and modified at runtime. LPARX, implemented as a C++ class library, is currently running on diverse MIMD platforms, including the Intel Paragon, Cray C‐90, IBM SP2, and networks of workstations running under PVM. Software may be developed and debugged on a singe‐processor workstation.