/pdf/scalable-molecular-dynamics-with-namd-3j7xyc70g4.pdf

Scalable Molecular Dynamics with NAMD

物件導向軟體之架構(Object-Oriented Software Construction)探討

A large number of MPI implementations are currently available, each of which emphasize different aspects of high-performance computing or are intended to solve a specific research problem. The result is a myriad of incompatible MPI implementations, all of which require separate installation, and the combination of which present significant logistical challenges for end users. Building upon prior research, and influenced by experience gained from the code bases of the LAM/MPI, LA-MPI, and FT-MPI projects, Open MPI is an all-new, production-quality MPI-2 implementation that is fundamentally centered around component concepts. Open MPI provides a unique combination of novel features previously unavailable in an open-source, production-quality implementation of MPI. Its component architecture provides both a stable platform for third-party research as well as enabling the run-time composition of independent software add-ons. This paper presents a high-level overview the goals, design, and implementation of Open MPI.

/pdf/open-mpi-goals-concept-and-design-of-a-next-generation-mpi-16i41y4jp9.pdf

Open MPI: Goals, Concept, and Design of a Next Generation MPI Implementation

[서평]「Component Software」 - Beyond Object-Oriented Programming -

The ability of performance technology to keep pace with the growing complexity of parallel and distributed systems depends on robust performance frameworks that can at once provide system-specific performance capabilities and support high-level performance problem solving Flexibility and portability in empirical methods and processes are influenced primarily by the strategies available for instrmentation and measurement, and how effectively they are integrated and composed This paper presents the TAU (Tuning and Analysis Utilities) parallel performance sytem and describe how it addresses diverse requirements for performance observation and analysis

/pdf/the-tau-parallel-performance-system-3fr3lax14z.pdf

The Tau Parallel Performance System

In this paper, we present performance analysis of two NASA applications using performance tools like Tuning and Analysis Utilities (TAU) and SGI MP Inside. MITgcmUV and OVERFLOW are two production-quality applications used extensively by scientists and engineers at NASA. MITgcmUV is a global ocean simulation model, developed by the Estimating the Circulation and Climate of the Ocean (ECCO) Consortium, for solving the fluid equations of motion using the hydrostatic approximation. OVERFLOW is a general-purpose Navier-Stokes solver for computational fluid dynamics (CFD) problems. Using these tools, we analyze the MPI functions (MPI_Sendrecv, MPI_Bcast, MPI_Reduce, MPI_Allreduce, MPI_Barrier, etc.) with respect to message size of each rank, time consumed by each function, and how ranks communicate. MPI communication is further analyzed by studying the performance of MPI functions used in these two applications as a function of message size and number of cores. Finally, we present the compute time, communication time, and I/O time as a function of the number of cores.

/pdf/performance-analysis-of-scientific-and-engineering-91mh3g6y2x.pdf

Performance Analysis of Scientific and Engineering Applications Using MPInside and TAU

Performance profiling generates measurement overhead during parallel program execution. Measurement overhead, in turn, introduces intrusion in a program's runtime performance behavior. Intrusion can be mitigated by controlling instrumentation degree, allowing a tradeoff of accuracy for detail. Alternatively, the accuracy in profile results can be improved by reducing the intrusion error due to measurement overhead. Models for compensation of measurement overhead in parallel performance profiling are described. An approach based on rational reconstruction is used to understand properties of compensation solutions for different parallel scenarios. From this analysis, a general algorithm for on-the-fly overhead assessment and compensation is derived.

/pdf/models-for-on-the-fly-compensation-of-measurement-overhead-xdq2ft8n60.pdf

Models for on-the-fly compensation of measurement overhead in parallel performance profiling

We introduce a tool that simplifies the performance assessment of input/output (I/O), memory, and Message Passing Interface (MPI) operations in a program under Linux. It describes how TAU improves the accuracy of measuring the extent of heap memory usage, and captures the volume and bandwidth of POSIX I/O performed in an un-instrumented program simply by modifying the command line for launching the parallel application. We describe the application of this tool to the Helios Rotorcraft Simulation Framework.

Simplifying Memory, I/O, and Communication Performance Assessment Using TAU

The influences of the operating system and system-specific effects on application performance are increasingly important considerations in high performance computing. OS kernel measurement is key to understanding the performance influences and the interrelationship of system and user-level performance factors. The KTAU (Kernel TAU) methodology and Linux-based framework provides parallel kernel performance measurement from both a kernel-wide and process-centric perspective. The first characterizes overall aggregate kernel performance for the entire system. The second characterizes kernel performance when it runs in the context of a particular process. KTAU extends the TAU performance system with kernel-level monitoring, while leveraging TAU's measurement and analysis capabilities. We explain the rational and motivations behind our approach, describe the KTAU design and implementation, and show working examples on multiple platforms demonstrating the versatility of KTAU in integrated system/application monitoring.

Integrated parallel performance views

Developing high performance OpenSHMEM applications routinely involves gaining a deeper understanding of software execution, yet there are numerous hurdles to gathering performance metrics in a production environment. Most OpenSHMEM performance profilers rely on the PSHMEM interface but PSHMEM is an optional and often unavailable feature. We present a tool that generates direct measurement performance profiles of OpenSHMEM applications even when PSHMEM is unavailable. The tool operates on dynamically linked and statically linked application binaries, does not require debugging symbols, and functions regardless of compiler optimization level. Integrated in the TAU Performance System, the tool uses automatically-generated wrapper libraries that intercept OpenSHMEM API calls to gather performance metrics with minimal overhead. Dynamically linked applications may use the tool without modifying the application binary in any way.

Sameer Shende

Papers

Performance Analysis of Scientific and Engineering Applications Using MPInside and TAU

Models for on-the-fly compensation of measurement overhead in parallel performance profiling

Simplifying Memory, I/O, and Communication Performance Assessment Using TAU

Integrated parallel performance views

Profiling Production OpenSHMEM Applications