Reducing consistency traffic and cache misses in the avalanche multiprocessor

Journal ArticleFor a parallel architecture to scale effectively, communication latency between processors must be avoided. We have found that the source of a large number of avoidable cache misses is the use of hardwired write-invalidate coherency protocols, which often exhibit high cache miss rates due to excessive invalidations and subsequent reloading of shared data. In the Avalanche project at the University of Utah, we are building a 64-node multiprocessor designed to reduce the end-to-end communication latency of both shared memory and message passing programs. As part of our design efforts, we are evaluating the potential performance benefits and implementation complexity of providing hardware support for multiple coherency protocols. Using a detailed architecture simulation of Avalanche, we have found that support for multiple consistency protocols can reduce the time parallel applications spend stalled on memory operations by up to 66% and overall execution time by up to 31%. Most of this reduction in memory stall time is due to a novel release-consistent multiple-writer write-update protocol implemented using a write state buffer

Avalanche: A communication and memory architecture for scalable parallel computing

technical reportAs the gap between processor and memory speeds widens, system designers will inevitably incorporate increasingly deep memory hierarchies to maintain the balance between processor and memory system performance. At the same time, most communication subsystems are permitted access only to main memory and not a processor's top level cache. As memory latencies increase, this lack of integration between the memory and communication systems will seriously impede interprocessor communication performance and limit effective scalability. In the Avalanche project we are redesigning the memory architecture of a commercial RISC multiprocessor, the HP PA-RISC 7100, to include a new multi-level context sensitive cache that is tightly coupled to the communication fabric. The primary goal of Avalanche's integrated cache and communication controller is attacking end to end communication latency in all of its forms. This includes cache misses induced by excessive invalidations and reloading of shared data by write-invalidate coherence protocols and cache misses induced by depositing incoming message data in main memory and faulting it into the cache. An execution-driven simulation study of Avalanche's architecture indicates that it can reduce cache stalls by 5-60% and overall execution times by 10-28%

Efficient openMP over sequentially consistent distributed shared memory systems

Nowadays clusters are one of the most used platforms in High Performance Computing and most programmers use the Message Passing Interface (MPI) library to program their applications in these distributed platforms getting their maximum performance, although it is a complex task. On the other side, OpenMP has been established as the de facto standard to program applications on shared memory platforms because it is easy to use and obtains good performance without too much effort. So, could it be possible to join both worlds? Could programmers use the easiness of OpenMP in distributed platforms? A lot of researchers think so. And one of the developed ideas is the distributed shared memory (DSM), a software layer on top of a distributed platform giving an abstract shared memory view to the applications. Even though it seems a good solution it also has some inconveniences. The memory coherence between the nodes in the platform is difficult to maintain (complex management, scalability issues, high overhead and others) and the latency of the remote-memory accesses which can be orders of magnitude greater than on a shared bus due to the interconnection network. Therefore this research improves the performance of OpenMP applications being executed on distributed memory platforms using a DSM with sequential consistency evaluating thoroughly the results from the NAS parallel benchmarks. The vast majority of designed DSMs use a relaxed consistency model because it avoids some major problems in the area. In contrast, we use a sequential consistency model because we think that showing these potential problems that otherwise are hidden may allow the finding of some solutions and, therefore, apply them to both models. The main idea behind this work is that both runtimes, the OpenMP and the DSM layer, should cooperate to achieve good performance, otherwise they interfere one each other trashing the final performance of applications. We develop three different contributions to improve the performance of these applications: (a) a technique to avoid false sharing at runtime, (b) a technique to mimic the MPI behaviour, where produced data is forwarded to their consumers and, finally, (c) a mechanism to avoid the network congestion due to the DSM coherence messages. The NAS Parallel Benchmarks are used to test the contributions. The results of this work shows that the false-sharing problem is a relative problem depending on each application. Another result is the importance to move the data flow outside of the critical path and to use techniques that forwards data as early as possible, similar to MPI, benefits the final application performance. Additionally, this data movement is usually concentrated at single points and affects the application performance due to the limited bandwidth of the network. Therefore it is necessary to provide mechanisms that allows the distribution of this data through the computation time using an otherwise idle network. Finally, results shows that the proposed contributions improve the performance of OpenMP applications on this kind of environments

Optimizing message-passing performance within symmetric multiprocessor systems

The Message Passing Interface (MPI) has been widely used in the area of parallel computing due to its portability, scalability, and ease of use. Message passing within Symmetric Multiprocessor (SMP) systems is an import part of any MPI library since it enables parallel programs to run efficiently on SMP systems, or clusters of SMP systems when combined with other ways of communication such as TCP/IP. Most message-passing implementations use a shared memory pool as an intermediate buffer to hold messages, some lock mechanisms to protect the pool, and some synchronization mechanism for coordinating the processes. However, the performance varies significantly depending on how these are implemented. The work here implements two SMP message-passing modules using lock-based and lock-free approaches for MPLi̲te, a compact library that implements a subset of the most commonly used MPI functions. Various optimization techniques have been used to optimize the performance. These two modules are evaluated using a communication performance analysis tool called NetPIPE, and compared with the implementations of other MPI libraries such as MPICH, MPICH2, LAM/MPI and MPI/PRO. Performance tools such as PAPI and VTune are used to gather some runtime information at the hardware level. This information together with some cache theory and the hardware configuration is used to explain various performance phenomena. Tests using a real application have shown the performance of the different implementations in real practice. These results all show that the improvements of the new techniques over existing implementations

Cloud-efficient modelling and simulation of magnetic nano materials

Scientific simulations are rarely attempted in a cloud due to the substantial performance costs of virtualization. Considerable communication overheads, intolerable latencies, and inefficient hardware emulation are the main reasons why this emerging technology has not been fully exploited. On the other hand, the progress of computing infrastructure nowadays is strongly dependent on perspective storage medium development, where efficient micromagnetic simulations play a vital role in future memory design. This thesis addresses both these topics by merging micromagnetic simulations with the latest OpenStack cloud implementation while providing a time and costeffective alternative to expensive computing centers. However, many challenges have to be addressed before a high-performance cloud platform emerges as a solution for problems in micromagnetic research communities. First, the best solver candidate has to be selected and further improved, particularly in the parallelization and process communication domain. Second, a 3-level cloud communication hierarchy needs to be recognized and each segment adequately addressed. The required steps include breaking the VMisolation for the host’s shared memory activation, cloud network-stack tuning, optimization, and efficient communication hardware integration. The project work concludes with practical measurements and confirmation of successfully implemented simulation into an open-source cloud environment. It is achieved that the renewed Magpar solver runs for the first time in the OpenStack cloud by using ivshmem for shared memory communication. Also, extensive measurements proved the effectiveness of our solutions, yielding from sixty percent to over ten times better results than those achieved in the standard cloud.Aufgrund der erheblichen Leistungskosten der Virtualisierung werden wissenschaftliche Simulationen in einer Cloud selten versucht. Beträchtlicher Kommunikationsaufwand, erhebliche Latenzen und ineffiziente Hardwareemulation sind die Hauptgründe, warum diese aufkommende Technologie nicht vollständig genutzt wurde. Andererseits hängt der Fortschritt der Computertechnologie heutzutage stark von der Entwicklung perspektivischer Speichermedien ab, bei denen effiziente mikromagnetische Simulationen eine wichtige Rolle für die zukünftige Speichertechnologie spielen. Diese Arbeit befasst sich mit diesen beiden Themen, indem mikromagnetische Simulationen mit der neuesten OpenStack Cloud-Implementierung zusammengeführt werden, um eine zeit- und kostengünstige Alternative zu teuren Rechenzentren bereitzustellen. Viele Herausforderungen müssen jedoch angegangen werden, bevor eine leistungsstarke Cloud-Plattform als Lösung für Probleme in mikromagnetischen Forschungsgemeinschaften entsteht. Zunächst muss der beste Kandidat für die Lösung ausgewählt und weiter verbessert werden, insbesondere im Bereich der Parallelisierung und Prozesskommunikation. Zweitens muss eine 3-stufige CloudKommunikationshierarchie erkannt und jedes Segment angemessen adressiert werden. Die erforderlichen Schritte umfassen das Aufheben der VM-Isolation, um den gemeinsam genutzten Speicher zwischen Cloud-Instanzen zu aktivieren, die Optimierung des Cloud-Netzwerkstapels und die effiziente Integration von Kommunikationshardware. Die praktische Arbeit endet mit Messungen und der Bestätigung einer erfolgreich implementierten Simulation in einer Open-Source Cloud-Umgebung. Als Ergebnis haben wir erreicht, dass der neu erstellte Magpar-Solver zum ersten Mal in der OpenStack Cloud ausgeführt wird, indem ivshmem für die Shared-Memory Kommunikation verwendet wird. Umfangreiche Messungen haben auch die Wirksamkeit unserer Lösungen bewiesen und von sechzig Prozent bis zu zehnmal besseren Ergebnissen als in der Standard Cloud geführt

Federating Heterogeneous Digital Libraries by Metadata Harvesting

This dissertation studies the challenges and issues faced in federating heterogeneous digital libraries (DLs) by metadata harvesting. The objective of federation is to provide high-level services (e.g. transparent search across all DLs) on the collective metadata from different digital libraries. There are two main approaches to federate DLs: distributed searching approach and harvesting approach. As the distributed searching approach replies on executing queries to digital libraries in real time, it has problems with scalability. The difficulty of creating a distributed searching service for a large federation is the motivation behind Open Archives Initiatives Protocols for Metadata Harvesting (OAI-PMH). OAI-PMH supports both data providers (repositories, archives) and service providers. Service providers develop value-added services based on the information collected from data providers. Data providers are simply collections of harvestable metadata. This dissertation examines the application of the metadata harvesting approach in DL federations. It addresses the following problems: (1) Whether or not metadata harvesting provides a realistic and scalable solution for DL federation. (2) What is the status of and problems with current data provider implementations, and how to solve these problems. (3) How to synchronize data providers and service providers. (4) How to build different types of federation services over harvested metadata. (5) How to create a scalable and reliable infrastructure to support federation services. The work done in this dissertation is based on OAI-PMH, and the results have influenced the evolution of OAI-PMH. However, the results are not limited to the scope of OAI-PMH. Our approach is to design and build key services for metadata harvesting and to deploy them on the Web. Implementing a publicly available service allows us to demonstrate how these approaches are practical. The problems posed above are evaluated by performing experiments over these services. To summarize the results of this thesis, we conclude that the metadata harvesting approach is a realistic and scalable approach to federate heterogeneous DLs. We present two models of building federation services: a centralized model and a replicated model. Our experiments also demonstrate that the repository synchronization problem can be addressed by push, pull, and hybrid push/pull models; each model has its strengths and weaknesses and fits a specific scenario. Finally, we present a scalable and reliable infrastructure to support the applications of metadata harvesting