M-VIA on the PowerPC architecture

One of the basic principles of cluster communication is to have the smallest cost in the time consumed on delivering messages between nodes. The Virtual Interface Architecture (VIA) is a communication protocol for system area networks (SAN) that bypasses much of the overhead of traditional network protocol stacks and provides more direct access to the network interface controller (NIC). The aim of our research was to investigate if VIA would perform well on PowerPC processors which have a different architecture than the previous processors used with VIA. For that reason, VIA was implemented on PowerPC and new driver support was added. The results indicate that VIA performs better than TCP/IP on large message sizes but not on small message sizes

Three pitfalls in Java performance evaluation

The Java programming language has known a remarkable growth over the last decade. This is partially due to the infrastructure required to run Java ap- plications on general purpose microprocessors: a Java virtual machine (VM). The VM ensures that Java applications are portable across different hardware platforms, because it shelters the applications from the underlying system. Hence the motto write once, run (almost) anywhere. Java applications are compiled to an intermediate form, called bytecode, and consist of a number of so-called class files. The virtual machine takes care of class loading, interpreting or compiling the bytecode to the native code of the underlying hardware platform, thread scheduling, garbage collection, etc. As such, during the execution of a Java application, the VM regularly intervenes to take care of housekeeping tasks and to optimise the application as it is executing. Furthermore, the specific implementation details of most virtual machines insert non-deterministic behaviour, not into the semantic part of the execution, but rather into the lower level execution. For example, to bring a Java application up to competitive speed with classical compiled programs written in languages such as C, the virtual machine needs to optimise Java bytecode. To limit the execution overhead, most virtual machines use a time sampling mechanism to determine the hot methods in the application. This introduces non-determinism, as over several runs, the methods are not always optimised at the same moment, nor is the set of optimised methods always the same. Other factors that introduce non-determinism are the thread scheduling, garbage collection, etc. It is readily seen that performance analysis of Java applications is not as simple as it seems at first, and warrants closer inspection. In this dissertation we are mainly interested in the behaviour of Java applications and their performance. In the course of this work, we uncovered three major pitfalls that were not taken into account by researchers when analysing Java performance prior to this work. We will briefly summarise the main achievements presented in this dissertation. The first pitfall we present involves the interaction between the virtual machine, the application and the input to the application. The performance for short running applications is shown to be mainly determined by the virtual machine. For longer running applications, this influence decreases, but remains tangible. We use statistical analysis, such as principal components analysis and cluster analysis (K-means and hierarchical clustering) to demonstrate and clarify the pitfall. By means of a large number of performance char- acteristics measured using hardware performance counters, five virtual machines and fourteen benchmarks with both a small and a large input size, we demonstrate that short running workloads are primarily clustered by virtual machines. Even for long running applications from the SPECjvm98 benchmark suite, the virtual machine still exerts a large influence on the observed behaviour at the microarchitectural level. This work has shown the need for both larger and longer running benchmarks than were available prior to it – this was (partially) met by the introduction of the DaCapo benchmark suite – as well as a careful consideration when setting up an experiment to avoid measuring the virtual machine, rather than the benchmark. Prior to this work, people were quite often using simulation with short running applications (to save time) for exploring Java performance. The second pitfall we uncover involves the analysis of performance numbers. During a survey of 50 papers published at premier conferences, such as OOPSLA, PLDI, CGO, ISMM and VEE, over the past seven years, we found that a variety of approaches are used, both for experimental design – for example, the input size, virtual machines, heap sizes, etc. – and, even more importantly, for data analysis – for example, using a best out of 3 performance number. New techniques are pitted against existing work using these prevalent approaches, and conclusions regarding their successfulness in beating prior state-of-the-art are based upon them. Given the fact that the execution of Java applications usually involves non-determinism in the virtual machine – for example, when determining which methods to optimise – it should come as no surprise that the lack of statistical rigour in these prevalent approaches leads to misleading or even incorrect conclusions. By this we mean that the conclusions are either not representative of what actually happens, or even contradict reality, as modelled in a statistical manner. To circumvent this pitfall, we propose a rigorous statistical approach that uses confidence intervals to both report and compare performance numbers. We also claim that sufficient experiments should be conducted to get a reliable performance measure. The non-determinism caused by the timer-based optimisation component in a virtual machine can be eliminated using so-called replay compilation. This technique will record a compilation plan during a first execution or profiling run of the application. During a second execution, the application is iterated twice: once to compile and optimise all methods found in the compilation plan, and a second time to perform the actual measurement. It turns out however that current practice of using either a single plan – corresponding to the best performing profiling run – or a combined plan choosing the methods that were optimised in, say, more than half the profiling runs, is no match for using multiple plans. The variability observed in the plans themselves is too large to capture in one of the current practices. Consequently, using multiple plans is definitely the better option. Moreover, this allows using a matched-pair approach in the data analysis, which results in tighter confidence intervals for the mean performance number. The third pitfall we examine is the usage of global performance numbers when tuning either an application or a virtual machine. We show that Java applications exhibit phase behaviour at the method level. This means that instances of the same method show more similarity to each other, behaviourwise, than to instances of other methods. A phase can then be identified as a set of sub-trees of the dynamic call-tree, with each sub-tree headed by the same method. We present an two-step algorithm that allows correlating hardware performance counter data in step 2 with the phases determined in step 1. The information obtained can be applied to show the programmer which methods perform worse than average, for example with respect to the number of cache misses they incur. In the dissertation, we pay particular attention to statistical rigour. For each pitfall, we use statistics to demonstrate its presence. Hopefully this work will encourage other researchers to use more rigour in their work as well

Trace-based Performance Analysis for Hardware Accelerators

This thesis presents how performance data from hardware accelerators can be included in event logs. It extends the capabilities of trace-based performance analysis to also monitor and record data from this novel parallelization layer. The increasing awareness to power consumption of computing devices has led to an interest in hybrid computing architectures as well. High-end computers, workstations, and mobile devices start to employ hardware accelerators to offload computationally intense and parallel tasks, while at the same time retaining a highly efficient scalar compute unit for non-parallel tasks. This execution pattern is typically asynchronous so that the scalar unit can resume other work while the hardware accelerator is busy. Performance analysis tools provided by the hardware accelerator vendors cover the situation of one host using one device very well. Yet, they do not address the needs of the high performance computing community. This thesis investigates ways to extend existing methods for recording events from highly parallel applications to also cover scenarios in which hardware accelerators aid these applications. After introducing a generic approach that is suitable for any API based acceleration paradigm, the thesis derives a suggestion for a generic performance API for hardware accelerators and its implementation with NVIDIA CUPTI. In a next step the visualization of event logs containing data from execution streams on different levels of parallelism is discussed. In order to overcome the limitations of classic performance profiles and timeline displays, a graph-based visualization using Parallel Performance Flow Graphs (PPFGs) is introduced. This novel technical approach is using program states in order to display similarities and differences between the potentially very large number of event streams and, thus, enables a fast way to spot load imbalances. The thesis concludes with the in-depth analysis of a case-study of PIConGPU---a highly parallel, multi-hybrid plasma physics simulation---that benefited greatly from the developed performance analysis methods.Diese Dissertation zeigt, wie der Ablauf von Anwendungsteilen, die auf Hardwarebeschleuniger ausgelagert wurden, als Programmspur mit aufgezeichnet werden kann. Damit wird die bekannte Technik der Leistungsanalyse von Anwendungen mittels Programmspuren so erweitert, dass auch diese neue Parallelitätsebene mit erfasst wird. Die Beschränkungen von Computersystemen bezüglich der elektrischen Leistungsaufnahme hat zu einer steigenden Anzahl von hybriden Computerarchitekturen geführt. Sowohl Hochleistungsrechner, aber auch Arbeitsplatzcomputer und mobile Endgeräte nutzen heute Hardwarebeschleuniger um rechenintensive, parallele Programmteile auszulagern und so den skalaren Hauptprozessor zu entlasten und nur für nicht parallele Programmteile zu verwenden. Dieses Ausführungsschema ist typischerweise asynchron: der Skalarprozessor kann, während der Hardwarebeschleuniger rechnet, selbst weiterarbeiten. Die Leistungsanalyse-Werkzeuge der Hersteller von Hardwarebeschleunigern decken den Standardfall (ein Host-System mit einem Hardwarebeschleuniger) sehr gut ab, scheitern aber an einer Unterstützung von hochparallelen Rechnersystemen. Die vorliegende Dissertation untersucht, in wie weit auch multi-hybride Anwendungen die Aktivität von Hardwarebeschleunigern aufzeichnen können. Dazu wird die vorhandene Methode zur Erzeugung von Programmspuren für hochparallele Anwendungen entsprechend erweitert. In dieser Untersuchung wird zuerst eine allgemeine Methodik entwickelt, mit der sich für jede API-gestützte Hardwarebeschleunigung eine Programmspur erstellen lässt. Darauf aufbauend wird eine eigene Programmierschnittstelle entwickelt, die es ermöglicht weitere leistungsrelevante Daten aufzuzeichnen. Die Umsetzung dieser Schnittstelle wird am Beispiel von NVIDIA CUPTI darstellt. Ein weiterer Teil der Arbeit beschäftigt sich mit der Darstellung von Programmspuren, welche Aufzeichnungen von den unterschiedlichen Parallelitätsebenen enthalten. Um die Einschränkungen klassischer Leistungsprofile oder Zeitachsendarstellungen zu überwinden, wird mit den parallelen Programmablaufgraphen (PPFGs) eine neue graphenbasisierte Darstellungsform eingeführt. Dieser neuartige Ansatz zeigt eine Programmspur als eine Folge von Programmzuständen mit gemeinsamen und unterchiedlichen Abläufen. So können divergierendes Programmverhalten und Lastimbalancen deutlich einfacher lokalisiert werden. Die Arbeit schließt mit der detaillierten Analyse von PIConGPU -- einer multi-hybriden Simulation aus der Plasmaphysik --, die in großem Maße von den in dieser Arbeit entwickelten Analysemöglichkeiten profiert hat

From experiment to design – fault characterization and detection in parallel computer systems using computational accelerators

This dissertation summarizes experimental validation and co-design studies conducted to optimize the fault detection capabilities and overheads in hybrid computer systems (e.g., using CPUs and Graphics Processing Units, or GPUs), and consequently to improve the scalability of parallel computer systems using computational accelerators. The experimental validation studies were conducted to help us understand the failure characteristics of CPU-GPU hybrid computer systems under various types of hardware faults. The main characterization targets were faults that are difficult to detect and/or recover from, e.g., faults that cause long latency failures (Ch. 3), faults in dynamically allocated resources (Ch. 4), faults in GPUs (Ch. 5), faults in MPI programs (Ch. 6), and microarchitecture-level faults with specific timing features (Ch. 7). The co-design studies were based on the characterization results. One of the co-designed systems has a set of source-to-source translators that customize and strategically place error detectors in the source code of target GPU programs (Ch. 5). Another co-designed system uses an extension card to learn the normal behavioral and semantic execution patterns of message-passing processes executing on CPUs, and to detect abnormal behaviors of those parallel processes (Ch. 6). The third co-designed system is a co-processor that has a set of new instructions in order to support software-implemented fault detection techniques (Ch. 7). The work described in this dissertation gains more importance because heterogeneous processors have become an essential component of state-of-the-art supercomputers. GPUs were used in three of the five fastest supercomputers that were operating in 2011. Our work included comprehensive fault characterization studies in CPU-GPU hybrid computers. In CPUs, we monitored the target systems for a long period of time after injecting faults (a temporally comprehensive experiment), and injected faults into various types of program states that included dynamically allocated memory (to be spatially comprehensive). In GPUs, we used fault injection studies to demonstrate the importance of detecting silent data corruption (SDC) errors that are mainly due to the lack of fine-grained protections and the massive use of fault-insensitive data. This dissertation also presents transparent fault tolerance frameworks and techniques that are directly applicable to hybrid computers built using only commercial off-the-shelf hardware components. This dissertation shows that by developing understanding of the failure characteristics and error propagation paths of target programs, we were able to create fault tolerance frameworks and techniques that can quickly detect and recover from hardware faults with low performance and hardware overheads

Optimization, high availability and redundancy in information communications and technology using networks and systems virtualization architectures

Mestrado em Engenharia InformáticaIn an era marked by the so-called technological revolution, where computing power has become a critical production factor, just like manpower was in the industrial revolution, very quickly this dispersal of computing power for numerous facilities and sites became unsustainable, both economically as well in terms of maintenance and management. This constringency led to the need of adopting new strategies for the provision of information systems equally capable but in a more consolidated way, while also increasing the desired levels of the classic set of information assurances: availability, confidentiality, authenticity and integrity. At this point enters a topic not as new as it may seem, virtualization, which after two decades of oblivion presents itself as the best candidate to solve the problem technology faces today. Throughout this thesis, it will be explained what this technology represents and what approach should be taken in the evolution of a systems architecture classical model into a model based in optimization, high availability, redundancy and consolidation of information communications and technology, using networks and systems virtualization. A number of good management principles to adopt will also be taken into account to ensure quality standards in providing services, culminating in a practical application of this model to the infrastructure of the company Metro do Porto, SA. Briefly, this document can almost be classified as a step by step manual for the understanding and implementation of this model, transversal to any infrastructure without extremely particular needs or constraints which derail conversion.Numa era marcada pela chamada revolução tecnológica, em que o poder de computação se tornou um factor crítico de produção, tal como a mão-de-obra o foi na revolução industrial, rapidamente esta dispersão do poder de computação por inúmeros equipamentos e locais tornou-se insustentável, quer ao nível económico como de manutenção e gestão. Este constrangimento levou à necessidade de adopção de novas estratégias para a disponibilização de sistemas de informação igualmente capazes mas de forma mais consolidada, procurando simultaneamente aumentar os níveis desejáveis do clássico paradigma dos factores a garantir na informação: disponibilidade, confidencialidade, autenticidade e integridade. É neste ponto que entra um tema não tão novo como parece, a virtualização, que após duas décadas de esquecimento se apresenta como o maior candidato à resolução do problema que a tecnologia enfrenta. Ao longo desta tese, será explicado o que esta tecnologia representa e qual a abordagem a ter na evolução de um modelo clássico de arquitectura de sistemas para um modelo baseado em optimização, alta disponibilidade, redundância e consolidação de tecnologias de informação e comunicações com recurso à virtualização de redes e sistemas. Serão igualmente tidos em conta um número de bons princípios de gestão a adoptar de forma a garantir parâmetros de qualidade na disponibilização de serviços, culminando numa aplicação prática de todo este modelo na infra-estrutura da empresa Metro do Porto, SA. Resumidamente, este documento pode ser classificado quase como um manual passo a passo de compreensão e implementação deste modelo, transversal a qualquer infra-estrutura sem constrangimentos ou necessidades extremamente particulares e que inviabilizem a conversão

Instruction level power consumption estimation for ArchC processors

Orientador: Rodolfo Jardim de AzevedoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A constante redução do tamanho e o conseqüente aumento do número de transistores em um mesmo chip faz com que a potência dissipada pelos circuitos digitais aumente exponencialmente. Esse fato, combinado com a crescente demanda por dispositivos portáteis, têm levado à uma crescente preocupação quanto ao consumo de energia. Quanto mais potência é dissipada mais calor é gerado e mais energia é gasta com o seu resfriamento. Como resultado, projetistas estão considerando cada vez mais o impacto de suas decisões nesse quesito. Atualmente, ADLs¹ têm sido utilizadas para projetar novos processadores. Essas linguagens descrevem o comportamento da arquitetura para cada ação ou instrução. ADLs, além de diminuirem o tempo de projeto, são úteis para descobrir problemas arquiteturais em um nível mais elevado. Nesse trabalho, foi desenvolvida uma ferramenta de estimativa de consumo de energia em nível de instrução utilizando-se como base a ADL ArchC e, como estudo de caso, um processador SPARCv8. Como resultado do uso da ferramenta desenvolvida, uma simulação de um programa com estimativa de consumo de energia pode ser realizada 100 vezes mais rápida, na média, em relação ao fluxo tradicionalAbstract: The constant reduction in size and consequential increase in number of transistors inside a chip causes an exponential growth in digital circuit power consumption. Combined with the growing demand for portable electronic devices, this has led to a rising concern about energy consumption. The more power is dissipated, the more heat is generated, and the more energy is spent in the cooling process. As a result, designers have been more and more considering the impact of their decisions on this matter. Currently, ADLs¹ are being used to design new processors. These languages describe the architectural behaviour for each action or instruction. Besides decreasing the time-to-market gap, ADLs are useful in discovering architectural problems at a higher level. This work presents an instruction leveI power estimation tool that uses ArchC ADL as a base, and a SPARCv8 processor as a case study. By using the developed tool, a simulation of a program with estimated power consumption can be accomplished 100 times faster, in average, than the traditional toolsMestradoSistemas de ComputaçãoMestre em Ciência da Computaçã

Overlapping of Communication and Computation and Early Binding: Fundamental Mechanisms for Improving Parallel Performance on Clusters of Workstations

This study considers software techniques for improving performance on clusters of workstations and approaches for designing message-passing middleware that facilitate scalable, parallel processing. Early binding and overlapping of communication and computation are identified as fundamental approaches for improving parallel performance and scalability on clusters. Currently, cluster computers using the Message-Passing Interface for interprocess communication are the predominant choice for building high-performance computing facilities, which makes the findings of this work relevant to a wide audience from the areas of high-performance computing and parallel processing. The performance-enhancing techniques studied in this work are presently underutilized in practice because of the lack of adequate support by existing message-passing libraries and are also rarely considered by parallel algorithm designers. Furthermore, commonly accepted methods for performance analysis and evaluation of parallel systems omit these techniques and focus primarily on more obvious communication characteristics such as latency and bandwidth. This study provides a theoretical framework for describing early binding and overlapping of communication and computation in models for parallel programming. This framework defines four new performance metrics that facilitate new approaches for performance analysis of parallel systems and algorithms. This dissertation provides experimental data that validate the correctness and accuracy of the performance analysis based on the new framework. The theoretical results of this performance analysis can be used by designers of parallel system and application software for assessing the quality of their implementations and for predicting the effective performance benefits of early binding and overlapping. This work presents MPI/Pro, a new MPI implementation that is specifically optimized for clusters of workstations interconnected with high-speed networks. This MPI implementation emphasizes features such as persistent communication, asynchronous processing, low processor overhead, and independent message progress. These features are identified as critical for delivering maximum performance to applications. The experimental section of this dissertation demonstrates the capability of MPI/Pro to facilitate software techniques that result in significant application performance improvements. Specific demonstrations with Virtual Interface Architecture and TCP/IP over Ethernet are offered

Resilient Design for Process and Runtime Variations

The main objective of this thesis is to tackle the impact of parameter variations in order to improve the chip performance and extend its lifetime