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| Author | : Mark J. Clement |
| Publisher | : |
| Total Pages | : 232 |
| Release | : 1994 |
| Genre | : Parallel programming (Computer science) |
| ISBN | : |
| Author | : Xingfu Wu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 336 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461551471 |
Performance Evaluation, Prediction and Visualization in Parallel Systems presents a comprehensive and systematic discussion of theoretics, methods, techniques and tools for performance evaluation, prediction and visualization of parallel systems. Chapter 1 gives a short overview of performance degradation of parallel systems, and presents a general discussion on the importance of performance evaluation, prediction and visualization of parallel systems. Chapter 2 analyzes and defines several kinds of serial and parallel runtime, points out some of the weaknesses of parallel speedup metrics, and discusses how to improve and generalize them. Chapter 3 describes formal definitions of scalability, addresses the basic metrics affecting the scalability of parallel systems, discusses scalability of parallel systems from three aspects: parallel architecture, parallel algorithm and parallel algorithm-architecture combinations, and analyzes the relations of scalability and speedup. Chapter 4 discusses the methodology of performance measurement, describes the benchmark- oriented performance test and analysis and how to measure speedup and scalability in practice. Chapter 5 analyzes the difficulties in performance prediction, discusses application-oriented and architecture-oriented performance prediction and how to predict speedup and scalability in practice. Chapter 6 discusses performance visualization techniques and tools for parallel systems from three stages: performance data collection, performance data filtering and performance data visualization, and classifies the existing performance visualization tools. Chapter 7 describes parallel compiling-based, search-based and knowledge-based performance debugging, which assists programmers to optimize the strategy or algorithm in their parallel programs, and presents visual programming-based performance debugging to help programmers identify the location and cause of the performance problem. It also provides concrete suggestions on how to modify their parallel program to improve the performance. Chapter 8 gives an overview of current interconnection networks for parallel systems, analyzes the scalability of interconnection networks, and discusses how to measure and improve network performances. Performance Evaluation, Prediction and Visualization in Parallel Systems serves as an excellent reference for researchers, and may be used as a text for advanced courses on the topic.
| Author | : Thomas Fahringer |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 279 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461313716 |
Automatic Performance Prediction of Parallel Programs presents a unified approach to the problem of automatically estimating the performance of parallel computer programs. The author focuses primarily on distributed memory multiprocessor systems, although large portions of the analysis can be applied to shared memory architectures as well. The author introduces a novel and very practical approach for predicting some of the most important performance parameters of parallel programs, including work distribution, number of transfers, amount of data transferred, network contention, transfer time, computation time and number of cache misses. This approach is based on advanced compiler analysis that carefully examines loop iteration spaces, procedure calls, array subscript expressions, communication patterns, data distributions and optimizing code transformations at the program level; and the most important machine specific parameters including cache characteristics, communication network indices, and benchmark data for computational operations at the machine level. The material has been fully implemented as part of P3T, which is an integrated automatic performance estimator of the Vienna Fortran Compilation System (VFCS), a state-of-the-art parallelizing compiler for Fortran77, Vienna Fortran and a subset of High Performance Fortran (HPF) programs. A large number of experiments using realistic HPF and Vienna Fortran code examples demonstrate highly accurate performance estimates, and the ability of the described performance prediction approach to successfully guide both programmer and compiler in parallelizing and optimizing parallel programs. A graphical user interface is described and displayed that visualizes each program source line together with the corresponding parameter values. P3T uses color-coded performance visualization to immediately identify hot spots in the parallel program. Performance data can be filtered and displayed at various levels of detail. Colors displayed by the graphical user interface are visualized in greyscale. Automatic Performance Prediction of Parallel Programs also includes coverage of fundamental problems of automatic parallelization for distributed memory multicomputers, a description of the basic parallelization strategy and a large variety of optimizing code transformations as included under VFCS.
| Author | : Mark Edward Crovella |
| Publisher | : |
| Total Pages | : 302 |
| Release | : 1994 |
| Genre | : |
| ISBN | : |
| Author | : Christoph W. Kessler |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 235 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3322878651 |
Distributed-memory multiprocessing systems (DMS), such as Intel's hypercubes, the Paragon, Thinking Machine's CM-5, and the Meiko Computing Surface, have rapidly gained user acceptance and promise to deliver the computing power required to solve the grand challenge problems of Science and Engineering. These machines are relatively inexpensive to build, and are potentially scalable to large numbers of processors. However, they are difficult to program: the non-uniformity of the memory which makes local accesses much faster than the transfer of non-local data via message-passing operations implies that the locality of algorithms must be exploited in order to achieve acceptable performance. The management of data, with the twin goals of both spreading the computational workload and minimizing the delays caused when a processor has to wait for non-local data, becomes of paramount importance. When a code is parallelized by hand, the programmer must distribute the program's work and data to the processors which will execute it. One of the common approaches to do so makes use of the regularity of most numerical computations. This is the so-called Single Program Multiple Data (SPMD) or data parallel model of computation. With this method, the data arrays in the original program are each distributed to the processors, establishing an ownership relation, and computations defining a data item are performed by the processors owning the data.
| Author | : Gangyi Zhu |
| Publisher | : |
| Total Pages | : 163 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
We start from predicting performance of the disk-based and in-situ parallel data analytics implemented in MapReduce-like frameworks. We take two distinct approaches towards performance prediction. We first expand SKOPE (a SKeleton framewOrk for Performance Exploration) with performance models for disk data read, cache performance, and page fault penalty. Second, an analytical performance model is also developed.
| Author | : Jidong Zhai |
| Publisher | : Springer Nature |
| Total Pages | : 259 |
| Release | : 2023-09-09 |
| Genre | : Computers |
| ISBN | : 9819943663 |
This book presents a hybrid static-dynamic approach for efficient performance analysis of parallel applications on HPC systems. Performance analysis is essential to finding performance bottlenecks and understanding the performance behaviors of parallel applications on HPC systems. However, current performance analysis techniques usually incur significant overhead. Our book introduces a series of approaches for lightweight performance analysis. We combine static and dynamic analysis to reduce the overhead of performance analysis. Based on this hybrid static-dynamic approach, we then propose several innovative techniques for various performance analysis scenarios, including communication analysis, memory analysis, noise analysis, computation analysis, and scalability analysis. Through these specific performance analysis techniques, we convey to readers the idea of using static analysis to support dynamic analysis. To gain the most from the book, readers should have a basic grasp of parallel computing, computer architecture, and compilation techniques.
| Author | : |
| Publisher | : IOS Press |
| Total Pages | : 4947 |
| Release | : |
| Genre | : |
| ISBN | : |
| Author | : Yongge Huáng |
| Publisher | : Nova Publishers |
| Total Pages | : 448 |
| Release | : 2008 |
| Genre | : Computers |
| ISBN | : 9781604561869 |
Supercomputers are used for highly calculation-intensive tasks such as problems involving quantum mechanical physics, weather forecasting, climate research (including research into global warming), molecular modelling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of aeroplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion), cryptanalysis, and the like. Major universities, military agencies and scientific research laboratories are heavy users. This book presents the latest research in the field from around the world.
| Author | : Vikram S. Adve |
| Publisher | : |
| Total Pages | : 34 |
| Release | : 1995 |
| Genre | : Assembling (Electronic computers) |
| ISBN | : |
Abstract: "To support the transition from programming languages in which parallelism and communication are explicit to high-level languages that rely on compilers to infer such details from data decomposition directives, tools for performance analysis require increased sophistication and integration with other components in the programming system. We explore integration of performance tools with compilers for data parallel languages by integrating the Rice Fortran 77D compiler and the Illinois Pablo Environment. This integration permits analysis and correlation of the compiler-generated code's dynamic behavior and performance with the original data parallel source code. We expect that our strategy can serve as a model for integration of other data parallel compilers and performance tools."
