The Parallel Debugging Tool (PDT) of the Annai programming environmentis developed within the Joint CSCS-ETH/NEC Collaboration in Parallel Processing [1]. Like the other components of the integrated environment, PDT aims to provide support for application developers to debug portable large-scale data-parallelprograms based on HPF and message-passing programs based on the MPI standard. PDT supports MPI event tracing for race detection and deterministic replay for manually parallelized MPI programs as well as for code generated with the advanced techniques of a data-parallel compiler. This paper describes the tracing and replaying mechanisms included in PDT as well as their efficiency by presenting execution time overheads for several benchmark programs running on the NEC Cenju-2/3 distributed-memory parallel computers.

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Our goal is to ease the parallelization of applications on distributed-memory parallel processors. Part of our team is implementing parallel kernels common to industrially significant applications using High Performance Fortran (HPF) and the Message Passing Interface (MPI). They are assisted in this activity by a second group developing an integrated tool environment, Annai, consisting of a parallelization support tool, a debugger, and a performance monitor and analyzer. These two groups interact closely, with application developers defining requirements and evaluating prototypes of the tool environment.The Annai environment is unique in providing a suite of generalpurpose tools for scientific application development, encompassing comprehensive support for programming irregular problems and the debugging and tuning of HPF and/or MPI-based parallel programs. Addressing application developer requirements, while making leading-edge technology available in a genuinely-usable form, has resulted in the timely provision of powerful parallel programming tools. This paper describes goals, achievements and perspectives of the project, illustrating with specific case studies of three application kernels how the tool environment assists in the parallelization process: development effort and resulting performance are discussed.

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