Performance-oriented Cloud Provisioning: Taxonomy and Survey

Cloud computing is being viewed as the technology of today and the future. Through this paradigm, the customers gain access to shared computing resources located in remote data centers that are hosted by cloud providers (CP). This technology allows for provisioning of various resources such as virtual machines (VM), physical machines, processors, memory, network, storage and software as per the needs of customers. Application providers (AP), who are customers of the CP, deploy applications on the cloud infrastructure and then these applications are used by the end-users. To meet the fluctuating application workload demands, dynamic provisioning is essential and this article provides a detailed literature survey of dynamic provisioning within cloud systems with focus on application performance. The well-known types of provisioning and the associated problems are clearly and pictorially explained and the provisioning terminology is clarified. A very detailed and general cloud provisioning classification is presented, which views provisioning from different perspectives, aiding in understanding the process inside-out. Cloud dynamic provisioning is explained by considering resources, stakeholders, techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table

Computational Caches

Caching is a well-known technique for speeding up computation. We cache data from file systems and databases; we cache dynamically generated code blocks; we cache page translations in TLBs. We propose to cache the act of computation, so that we can apply it later and in different contexts. We use a state-space model of computation to support such caching, involving two interrelated parts: speculatively memoized predicted/resultant state pairs that we use to accelerate sequential computation, and trained probabilistic models that we use to generate predicted states from which to speculatively execute. The key techniques that make this approach feasible are designing probabilistic models that automatically focus on regions of program execution state space in which prediction is tractable and identifying state space equivalence classes so that predictions need not be exact.Engineering and Applied Science

Operating System Support for Redundant Multithreading

Failing hardware is a fact and trends in microprocessor design indicate that the fraction of hardware suffering from permanent and transient faults will continue to increase in future chip generations. Researchers proposed various solutions to this issue with different downsides: Specialized hardware components make hardware more expensive in production and consume additional energy at runtime. Fault-tolerant algorithms and libraries enforce specific programming models on the developer. Compiler-based fault tolerance requires the source code for all applications to be available for recompilation. In this thesis I present ASTEROID, an operating system architecture that integrates applications with different reliability needs. ASTEROID is built on top of the L4/Fiasco.OC microkernel and extends the system with Romain, an operating system service that transparently replicates user applications. Romain supports single- and multi-threaded applications without requiring access to the application's source code. Romain replicates applications and their resources completely and thereby does not rely on hardware extensions, such as ECC-protected memory. In my thesis I describe how to efficiently implement replication as a form of redundant multithreading in software. I develop mechanisms to manage replica resources and to make multi-threaded programs behave deterministically for replication. I furthermore present an approach to handle applications that use shared-memory channels with other programs. My evaluation shows that Romain provides 100% error detection and more than 99.6% error correction for single-bit flips in memory and general-purpose registers. At the same time, Romain's execution time overhead is below 14% for single-threaded applications running in triple-modular redundant mode. The last part of my thesis acknowledges that software-implemented fault tolerance methods often rely on the correct functioning of a certain set of hardware and software components, the Reliable Computing Base (RCB). I introduce the concept of the RCB and discuss what constitutes the RCB of the ASTEROID system and other fault tolerance mechanisms. Thereafter I show three case studies that evaluate approaches to protecting RCB components and thereby aim to achieve a software stack that is fully protected against hardware errors

The parallel event loop model and runtime: a parallel programming model and runtime system for safe event-based parallel programming

Recent trends in programming models for server-side development have shown an increasing popularity of event-based single- threaded programming models based on the combination of dynamic languages such as JavaScript and event-based runtime systems for asynchronous I/O management such as Node.JS. Reasons for the success of such models are the simplicity of the single-threaded event-based programming model as well as the growing popularity of the Cloud as a deployment platform for Web applications. Unfortunately, the popularity of single-threaded models comes at the price of performance and scalability, as single-threaded event-based models present limitations when parallel processing is needed, and traditional approaches to concurrency such as threads and locks don't play well with event-based systems. This dissertation proposes a programming model and a runtime system to overcome such limitations by enabling single-threaded event-based applications with support for speculative parallel execution. The model, called Parallel Event Loop, has the goal of bringing parallel execution to the domain of single-threaded event-based programming without relaxing the main characteristics of the single-threaded model, and therefore providing developers with the impression of a safe, single-threaded, runtime. Rather than supporting only pure single-threaded programming, however, the parallel event loop can also be used to derive safe, high-level, parallel programming models characterized by a strong compatibility with single-threaded runtimes. We describe three distinct implementations of speculative runtimes enabling the parallel execution of event-based applications. The first implementation we describe is a pessimistic runtime system based on locks to implement speculative parallelization. The second and the third implementations are based on two distinct optimistic runtimes using software transactional memory. Each of the implementations supports the parallelization of applications written using an asynchronous single-threaded programming style, and each of them enables applications to benefit from parallel execution

Machine Learning in Compiler Optimization

In the last decade, machine learning based compilation has moved from an an obscure research niche to a mainstream activity. In this article, we describe the relationship between machine learning and compiler optimisation and introduce the main concepts of features, models, training and deployment. We then provide a comprehensive survey and provide a road map for the wide variety of different research areas. We conclude with a discussion on open issues in the area and potential research directions. This paper provides both an accessible introduction to the fast moving area of machine learning based compilation and a detailed bibliography of its main achievements

The parallel event loop model and runtime: a parallel programming model and runtime system for safe event-based parallel programming

Recent trends in programming models for server-side development have shown an increasing popularity of event-based single- threaded programming models based on the combination of dynamic languages such as JavaScript and event-based runtime systems for asynchronous I/O management such as Node.JS. Reasons for the success of such models are the simplicity of the single-threaded event-based programming model as well as the growing popularity of the Cloud as a deployment platform for Web applications. Unfortunately, the popularity of single-threaded models comes at the price of performance and scalability, as single-threaded event-based models present limitations when parallel processing is needed, and traditional approaches to concurrency such as threads and locks don't play well with event-based systems. This dissertation proposes a programming model and a runtime system to overcome such limitations by enabling single-threaded event-based applications with support for speculative parallel execution. The model, called Parallel Event Loop, has the goal of bringing parallel execution to the domain of single-threaded event-based programming without relaxing the main characteristics of the single-threaded model, and therefore providing developers with the impression of a safe, single-threaded, runtime. Rather than supporting only pure single-threaded programming, however, the parallel event loop can also be used to derive safe, high-level, parallel programming models characterized by a strong compatibility with single-threaded runtimes. We describe three distinct implementations of speculative runtimes enabling the parallel execution of event-based applications. The first implementation we describe is a pessimistic runtime system based on locks to implement speculative parallelization. The second and the third implementations are based on two distinct optimistic runtimes using software transactional memory. Each of the implementations supports the parallelization of applications written using an asynchronous single-threaded programming style, and each of them enables applications to benefit from parallel execution

Kiihdytetyn laskennan ajoituksen ja energiankulutuksen simulointi

As the increase in the sequential processing performance of general-purpose central processing units has slowed down dramatically, computer systems have been moving towards increasingly parallel and heterogeneous architectures. Modern graphics processing units have emerged as one of the first affordable platforms for data-parallel processing. Due to their closed nature, it has been difficult for software developers to observe the performance and energy efficiency characteristics of the execution of applications of graphics processing units. In this thesis, we have explored different tools and methods for observing the execution of accelerated processing on graphics processing units. We have found that hardware vendors provide interfaces for observing the timing of events that occur on the host platform and aggregated performance metrics of execution on the graphics processing units to some extent. However, more fine-grained details of execution are currently available only by using graphics processing unit simulators. As a proof-of-concept, we have studied a functional graphics processing unit simulator as a tool for understanding the energy efficiency of accelerated processing. The presented energy estimation model and simulation method has been validated against a face detection application. The difference between the estimated and measured dynamic energy consumption in this case was found to be 5.4%. Functional simulators appear to be accurate enough to be used for observing the energy efficiency of graphics processing unit accelerated processing in certain use-cases.Suorittimien sarjallisen suorituskyvyn kasvun hidastuessa tietokonejärjestelmät ovat siirtymässä kohti rinnakkaislaskentaa ja heterogeenisia arkkitehtuureja. Modernit grafiikkasuorittimet ovat yleistyneet ensimmäisinä huokeina alustoina yleisluonteisen kiihdytetyn datarinnakkaisen laskennan suorittamiseen. Grafiikkasuorittimet ovat usein suljettuja alustoja, minkä takia ohjelmistokehittäjien on vaikea havainnoida tarkempia yksityiskohtia suorituksesta liittyen laskennan suorituskykyyn ja energian kulutukseen. Tässä työssä on tutkittu erilaisia työkaluja ja tapoja tarkkailla ohjelmien kiihdytettyä suoritusta grafiikkasuorittimilla. Laitevalmistajat tarjoavat joitakin rajapintoja tapahtumien ajoituksen havainnointiin sekä isäntäalustalla että grafiikkasuorittimella. Laskennan tarkempaan havainnointiin on kuitenkin usein käytettävä grafiikkasuoritinsimulaattoreita. Työn kokeellisessa osuudessa työssä on tutkittu funktionaalisten grafiikkasuoritinsimulaattoreiden käyttöä työkaluna grafiikkasuorittimella kiihdytetyn laskennan energiantehokkuuden arvioinnissa. Työssä on malli grafiikkasuorittimen energian kulutuksen arviontiin. Arvion validointiin on käytetty kasvontunnistussovellusta. Mittauksissa arvioidun ja mitatun energian kulutuksen eroksi mitattiin 5.4%. Funktionaaliset simulaattorit ovat mittaustemme perusteella tietyissä käyttötarkoituksissa tarpeeksi tarkkoja grafiikkasuorittimella kiihdytetyn laskennan energiatehokkuuden arviointiin