Quantifying the Performance Differences Between PVM and TreadMarks

We compare two systems for parallel programming on networks of workstations: Parallel Virtual Machine (PVM) a message passing system, and TreadMarks, a software distributed shared memory (DSM) system. We present results for eight applications that were implemented using both systems. The programs are Water and Barnes-Hut from the SPLASH benchmark suite; 3-D FFT, Integer Sort (IS) and Embarrassingly Parallel (EP) from the NAS benchmarks; ILINK, a widely used genetic linkage analysis program; and Successive Over-Relaxation (SOR) and Traveling Salesman (TSP). Two different input data sets were used for five of the applications. We use two execution environments. The first is an 155 Mbps ATM network with eight Sparc-20 model 61 workstations; the second is an eight processor IBM SP/2. The differences in speedup between TreadMarks and PVM are dependent on the application, and, only to much a lesser extent, on the platform and the data set used. In particular, the TreadMarks speedup for six of the eight applications is within 15% of that achieved with PVM. For one application, the difference in speedup is between 15% and 30%, and for one application, the difference is around 50%. More important than the actual differences in speedups, we investigate the causes behind these differences. The cost of sending and receiving messages on current networks of workstations is very high, and previous work has identified communication costs as the primary source of overhead in software DSM implementations. The observed performance differences between PVM and TreadMarks are therefore primarily a result of differences in the amount of communication between the two systems. We identified four factors that contribute to the larger amount of communication in TreadMarks:1) extra messages due to the separation of synchronization and data transfer, 2) extra messages to handle access misses caused by the use of an invalidate protocol, 3) false sharing, and 4) d iff accumulation for migratory data. We have quantified the effect of the last three factors by measuring the performance gain when each is eliminated. Because the separation of synchronization and data transfer is a fundamental characteristic of the shared memory model, there is no way to measure its contribution to performance without completely deviating from the shared memory model. Of the three remaining factors, TreadMarks’ inability to send data belonging to different pages in a single message is the most important. The effect of false sharing is quite limited. Reducing diff accumulation benefits migratory data only when the diffs completely overlap. When these performance impediments are removed, all of the TreadMarks programs perform within 25% of PVM, and for six out of eight experiments, TreadMarks is less than 5% slower than PVM

OpenMP on Networks of SMPs

In this paper, we present the first system that implements OpenMP on a network of shared-memory multiprocessors. This system enables the programmer to rely on a single, standard, shared-memory API for parallelization within a multiprocessor and between multiprocessors. It is implemented via a translator that converts OpenMP directives to appropriate calls to a modified version of the TreadMarks software distributed memory system (SDSM). In contrast to previous SDSM systems for SMPs, the modified TreadMarks uses POSIX threads for parallelism within an SMP node. This approach greatly simplifies the changes required to the SDSM in order to exploit the intra-node hardware shared memory. We present performance results for six applications (SPLASH-2 Barnes-Hut andWater, NAS 3D-FFT, SOR, TSP and MGS) running on an SP2 with four four-processor SMP nodes. A comparison between the threaded implementation and the original implementation of TreadMarks shows that using the hardware shared memory within an SMP node significantly reduces the amount of data and the number of messages transmitted between nodes, and consequently achieves speedups up to 30% better than the original versions. We also compare SDSM against message passing. Overall, the speedups of multithreaded TreadMarks programs are within 7–30% of the MPI versions

Run-time Support for Distributed Object Sharing in Safe Programming Languages

We present a new run-time system that supports object sharing in a distributed system. The key insight in this system is that a handle-based implementation of such a system enables effcient and transparent sharing of data with both fine-grained and coarse-grained access patterns. In addition, it supports effcient execution of garbage-collected programs. In contrast, conventional distributed shared memory (DSM) systems are limited to providing only one granularity with good performance, and have experienced diffculty in effciently supporting garbage collection. A safe language, in which no pointer arithmetic is allowed, can transparently be compiled into a handle-based system and constitutes its preferred mode of use. A programmer can also directly use a handle-based programming model that avoids pointer arithmetic on the handles, and achieve the same performance but without the programming benefits of a safe programming language. This new run-time system, DOSA (Distributed Object Sharing Architecture), provides a shared object space abstraction rather than a shared address space abstraction. The key to its effciency is the observation that a handle-based distributed implementation permits VM-based access and modification detection without suffering false sharing for fine-grained access patterns. We compare DOSA to TreadMarks, a conventional DSM system that is effcient at handling coarse-grained sharing. The performance of fine-grained applications and garbage-collected applications is considerably better than in TreadMarks. The performance of coarse-grained applications is nearly as good as in TreadMarks. Since the performance of such applications is already good in TreadMarks, we consider this an acceptable performance penalty

Eureka: a distributed shared memory system based on the Lazy Data Merging consistency model

Distributed Shared Memory (DSM) provides an abstraction of shared memory on a network of workstations. Problems with existing DSM systems are lack of portability due to compiler and/or operating system modification requirements, and reduced performance due to significant synchronization and communication costs when compared to their message passing counterparts (e.g., PVM and MPI). Our approach was to introduce a new DSM consistency model, Lazy Data Merging (LDM), which extends Data Merging (DM). LDM is optimized for software runtime implementations and differs from DM by 'lazily' placing data updates across the communication network only when they are required. It is our belief that LDM can significantly reduce communication costs, particularly for applications that make extensive use of locks. We have completed the design of "Eureka", a prototype DSM system that provides a software implementation of the LDM consistency model. To ensure portability and efficiency we use only standard UniXTM system calls and a publicly available software thread package, Cthreads, from the University of Utah. Furthermore, we have implemented and tested some of Eureka's core components, specifically, the set of communication and hybrid (Invalidate/Update) coherence primitives, which are essential for follow on work in building the complete DSM system. The question of efficiency is still an open problem, because we did not compare Eureka with other DSM implementations.http://archive.org/details/eurekadistribute1094535209NANABrazilian Navy author

High-performance all-software distributed shared memory

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (p. 165-172).by Kirk Lauritz Johnson.Ph.D

Run-time support for parallel object-oriented computing: the NIP lazy task creation technique and the NIP object-based software distributed shared memory

PhD ThesisAdvances in hardware technologies combined with decreased costs have started a trend towards massively parallel architectures that utilise commodity components. It is thought unreasonable to expect software developers to manage the high degree of parallelism that is made available by these architectures. This thesis argues that a new programming model is essential for the development of parallel applications and presents a model which embraces the notions of object-orientation and implicit identification of parallelism. The new model allows software engineers to concentrate on development issues, using the object-oriented paradigm, whilst being freed from the burden of explicitly managing parallel activity. To support the programming model, the semantics of an execution model are defined and implemented as part of a run-time support system for object-oriented parallel applications. Details of the novel techniques from the run-time system, in the areas of lazy task creation and object-based, distributed shared memory, are presented. The tasklet construct for representing potentially parallel computation is introduced and further developed by this thesis. Three caching techniques that take advantage of memory access patterns exhibited in object-oriented applications are explored. Finally, the performance characteristics of the introduced run-time techniques are analysed through a number of benchmark applications

Efficient Home-Based protocols for reducing asynchronous communication in shared virtual memory systems

En la presente tesis se realiza una evaluación exhaustiva de ls Sistemas de Memoria Distribuida conocidos como Sistemas de Memoria Virtual Compartida. Este tipo de sistemas posee características que los hacen especialmente atractivos, como son su relativo bajo costo, alta portabilidad y paradigma de progración de memoria compartida. La evaluación consta de dos partes. En la primera se detallan las bases de diseño y el estado del arte de la investigación sobre este tipo de sistemas. En la segunda, se estudia el comportamiento de un conjunto representativo de cargas paralelas respecto a tres ejes de caracterización estrechamente relacionados con las prestaciones en estos sistemas. Mientras que la primera parte apunta la hipótesis de que la comunicación asíncrona es una de las principales causas de pérdida de prestaciones en los Sistemas de Memoria Virtual Compartida, la segunda no sólo la confirma, sino que ofrece un detallado análisis de las cargas del que se obteiene información sobre la potencial comunicación asíncrona atendiendo a diferentes parámetros del sistema. El resultado de la evaluación se utiliza para proponer dos nuevos protocolos para el funcionamiento de estos sistemas que utiliza un mínimo de recursos de hardware, alcanzando prestaciones similares e incluso superiores en algunos casos a sistemas que utilizan circuitos hardware de propósito específico para reducir la comunicación asíncrona. En particular, uno de los protocolos propuestos es comparado con una reconocida técnica hardware para reducir la comunicación asíncrona, obteniendo resultados satisfactorios y complementarios a la técnica comparada. Todos los modelos y técnicas usados en este trabajo han sido implementados y evalados utilizando un nuevo entorno de simulación desarollado en el contexto de este trabajo.Petit Martí, SV. (2003). Efficient Home-Based protocols for reducing asynchronous communication in shared virtual memory systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/2908Palanci

Parallel and distributed computing techniques in biomedical engineering

Master'sMASTER OF ENGINEERIN

Distributed Shared Memory based Live VM Migration

Cloud computing is the new trend in computing services and IT industry, this computing paradigm has numerous benefits to utilize IT infrastructure resources and reduce services cost. The key feature of cloud computing depends on mobility and scalability of the computing resources, by managing virtual machines. The virtualization decouples the software from the hardware and manages the software and hardware resources in an easy way without interruption of services. Live virtual machine migration is an essential tool for dynamic resource management in current data centers. Live virtual machine is defined as the process of moving a running virtual machine or application between different physical machines without disconnecting the client or application. Many techniques have been developed to achieve this goal based on several metrics (total migration time, downtime, size of data sent and application performance) that are used to measure the performance of live migration. These metrics measure the quality of the VM services that clients care about, because the main goal of clients is keeping the applications performance with minimum service interruption. The pre-copy live VM migration is done in four phases: preparation, iterative migration, stop and copy, and resume and commitment. During the preparation phase, the source and destination physical servers are selected, the resources in destination physical server are reserved, and the critical VM is selected to be migrated. The cloud manager responsibility is to make all of these decisions. VM state migration takes place and memory state is transferred to the target node during iterative migration phase. Meanwhile, the migrated VM continues to execute and dirties its memory. In the stop and copy phase, VM virtual CPU is stopped and then the processor and network states are transferred to the destination host. Service downtime results from stopping VM execution and moving the VM CPU and network states. Finally in the resume and commitment phase, the migrated VM is resumed running in the destination physical host, the remaining memory pages are pulled by destination machine from the source machine. The source machine resources are released and eliminated. In this thesis, pre-copy live VM migration using Distributed Shared Memory (DSM) computing model is proposed. The setup is built using two identical computation nodes to construct all the proposed environment services architecture namely the virtualization infrastructure (Xenserver6.2 hypervisor), the shared storage server (the network file system), and the DSM and High Performance Computing (HPC) cluster. The custom DSM framework is based on a low latency memory update named Grappa. Moreover, HPC cluster is used to parallelize the work load by using CPUs computation nodes. HPC cluster employs OPENMPI and MPI libraries to support parallelization and auto-parallelization. The DSM allows the cluster CPUs to access the same memory space pages resulting in less memory data updates, which reduces the amount of data transferred through the network. The thesis proposed model achieves a good enhancement of the live VM migration metrics. Downtime is reduced by 50 % in the idle workload of Windows VM and 66.6% in case of Ubuntu Linux idle workload. In general, the proposed model not only reduces the downtime and the total amount of data sent, but also does not degrade other metrics like the total migration time and the applications performance

Design and implementation of a multi-purpose cluster system NIU

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 209-221).by Boon Seong Ang.Ph.D