Data-Flow Analysis for MPI Programs

Abstract

Message passing via MPI is widely used in singleprogram, multiple-data (SPMD) parallel programs. Existing data-flow frameworks do not model the semantics of message-passing SPMD programs, which can result in less precise and even incorrect analysis results. We present a data-flow analysis framework for performing interprocedural analysis of message-passing SPMD programs. The framework is based on the MPI-ICFG representation, which is an interprocedural control-flow graph (ICFG) augmented with communication edges between possible send and receive pairs and partial context sensitivity.We show how to formulate nonseparable data-flow analyses within our framework using reaching constants as a canonical example. We also formulate and provide experimental results for the nonseparable analysis, activity analysis. Activity analysis is a domain-specific analysis used to reduce the computation and storage requirements for automatically differentiated MPI programs. Automatic differentiation is important for application domains such as climate modeling, electronic device simulation, oil reservoir simulation, medical treatment planning and computational economics to name a few. Our experimental results show that using the MPI-ICFG data-flow analysis framework improves the precision of activity analysis and as a result significantly reduces memory requirements for the automatically differentiated versions of a set of parallel benchmarks, including some of the NAS Parallel Benchmarks.

Parallel Framework for Earthquake Induced Response Computation of the Sdof Structure

“…ether net, with LINUX 9 on each computer, programming language used was Fortran 77 with the latest MPICH version, in which one computer acted like the Master computer and the other one was a worker. It is to mention here that the Master computer also worked as a worker after distribution of the tasks to workers and then it also got the results from the Worker and displayed them after organization (Strout et al 2006;MPI 1997).…”

Static Approximation of MPI Communication Graphs for Optimized Process Placement

“…However, they have limitations that prevent their application to the problem described. Noted by multiple sources are the SPMD semantics of MPI [5,18,25]. The SPMD semantics are important as they largely define the methods that can be, and are, used to perform communication analysis.…”

“…The SPMD semantics are important as they largely define the methods that can be, and are, used to perform communication analysis. MPI-CFG [24] and later MPI-ICFG [18,25] annotate control-flow graphs (CFGs) with process sensitive traversals and communication edges between matched send and receive statements. Backward slicing is performed on the pure CFG to simplify expressions that indirectly reference process rank in the call parameter.…”

An enhanced flow analysis technique for detecting unreachability faults in concurrent systems

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