Parallel architectures and runtime systems co-design for task-based programming models

The increasing parallelism levels in modern computing systems has extolled the need for a holistic vision when designing multiprocessor architectures taking in account the needs of the programming models and applications. Nowadays, system design consists of several layers on top of each other from the architecture up to the application software. Although this design allows to do a separation of concerns where it is possible to independently change layers due to a well-known interface between them, it is hampering future systems design as the Law of Moore reaches to an end. Current performance improvements on computer architecture are driven by the shrinkage of the transistor channel width, allowing faster and more power efficient chips to be made. However, technology is reaching physical limitations were the transistor size will not be able to be reduced furthermore and requires a change of paradigm in systems design. This thesis proposes to break this layered design, and advocates for a system where the architecture and the programming model runtime system are able to exchange information towards a common goal, improve performance and reduce power consumption. By making the architecture aware of runtime information such as a Task Dependency Graph (TDG) in the case of dataflow task-based programming models, it is possible to improve power consumption by exploiting the critical path of the graph. Moreover, the architecture can provide hardware support to create such a graph in order to reduce the runtime overheads and making possible the execution of fine-grained tasks to increase the available parallelism. Finally, the current status of inter-node communication primitives can be exposed to the runtime system in order to perform a more efficient communication scheduling, and also creates new opportunities of computation and communication overlap that were not possible before. An evaluation of the proposals introduced in this thesis is provided and a methodology to simulate and characterize the application behavior is also presented.El aumento del paralelismo proporcionado por los sistemas de cómputo modernos ha provocado la necesidad de una visión holística en el diseño de arquitecturas multiprocesador que tome en cuenta las necesidades de los modelos de programación y las aplicaciones. Hoy en día el diseño de los computadores consiste en diferentes capas de abstracción con una interfaz bien definida entre ellas. Las limitaciones de esta aproximación junto con el fin de la ley de Moore limitan el potencial de los futuros computadores. La mayoría de las mejoras actuales en el diseño de los computadores provienen fundamentalmente de la reducción del tamaño del canal del transistor, lo cual permite chips más rápidos y con un consumo eficiente sin apenas cambios fundamentales en el diseño de la arquitectura. Sin embargo, la tecnología actual está alcanzando limitaciones físicas donde no será posible reducir el tamaño de los transistores motivando así un cambio de paradigma en la construcción de los computadores. Esta tesis propone romper este diseño en capas y abogar por un sistema donde la arquitectura y el sistema de tiempo de ejecución del modelo de programación sean capaces de intercambiar información para alcanzar una meta común: La mejora del rendimiento y la reducción del consumo energético. Haciendo que la arquitectura sea consciente de la información disponible en el modelo de programación, como puede ser el grafo de dependencias entre tareas en los modelos de programación dataflow, es posible reducir el consumo energético explotando el camino critico del grafo. Además, la arquitectura puede proveer de soporte hardware para crear este grafo con el objetivo de reducir el overhead de construir este grado cuando la granularidad de las tareas es demasiado fina. Finalmente, el estado de las comunicaciones entre nodos puede ser expuesto al sistema de tiempo de ejecución para realizar una mejor planificación de las comunicaciones y creando nuevas oportunidades de solapamiento entre cómputo y comunicación que no eran posibles anteriormente. Esta tesis aporta una evaluación de todas estas propuestas, así como una metodología para simular y caracterizar el comportamiento de las aplicacionesPostprint (published version

Modelli e strumenti di programmazione parallela per piattaforme many-core

The negotiation between power consumption, performance, programmability, and portability drives all computing industry designs, in particular the mobile and embedded systems domains. Two design paradigms have proven particularly promising in this context: architectural heterogeneity and many-core processors. Parallel programming models are key to effectively harness the computational power of heterogeneous many-core SoC. This thesis presents a set of techniques and HW/SW extensions that enable performance improvements and that simplify programmability for heterogeneous many-core platforms. The thesis contributions cover vertically the entire software stack for many-core platforms, from hardware abstraction layers running on top of bare-metal, to programming models; from hardware extensions for efficient parallelism support to middleware that enables optimized resource management within many-core platforms. First, we present mechanisms to decrease parallelism overheads on parallel programming runtimes for many-core platforms, targeting fine-grain parallelism. Second, we present programming model support that enables the offload of computational kernels within heterogeneous many-core systems. Third, we present a novel approach to dynamically sharing and managing many-core platforms when multiple applications coded with different programming models execute concurrently. All these contributions were validated using STMicroelectronics STHORM, a real embodiment of a state-of-the-art many-core system. Hardware extensions and architectural explorations were explored using VirtualSoC, a SystemC based cycle-accurate simulator of many-core platforms

Piattaforme multicore e integrazione tri-dimensionale: analisi architetturale e ottimizzazione

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.I sistemi integrati moderni sono architetture many-core, in cui spesso lo spazio di memoria è condiviso fra i processori. Per ridurre i consumi, molte di queste architetture sostituiscono le cache dati con memorie scratchpad gestite in software, per massimizzarne la località alle CPU e aumentare le performance. Questo significa che i dati devono essere spostati manualmente da parte del programmatore. Inoltre, tradurre in perfomance l’enorme parallelismo potenziale delle piattaforme many-core non è semplice. Per supportare la programmazione, diversi programming model sono stati proposti, e siccome lavorano ad un alto livello di astrazione, sfruttano delle librerie di runtime che forniscono servizi di base quali sincronizzazione, allocazione della memoria, threading. Queste librerie hanno un costo, che nei sistemi integrati è troppo elevato e ostacola il raggiungimento delle piene performance. Questa tesi analizza come un programming model ad alto livello di astrazione – OpenMP – possa essere efficientemente supportato, se il suo stack software viene adattato per sfruttare al meglio la piattaforma sottostante. In una prima parte, studio diversi meccanismi di sincronizzazione e comunicazione fra thread paralleli, portati sulle piattaforme many-core. In seguito, li utilizzo per scrivere un runtime di supporto a OpenMP che sia il più possibile efficente e “leggero” e che supporti paradigmi di parallelismo multi-livello e irregolare, spesso presenti nelle applicazioni moderne. Una seconda parte della tesi esplora le architetture eterogenee, ossia con acceleratori hardware. Queste architetture soffrono di problematiche sia i) per il processo di design della piattaforma, che ii) di scalabilità della piattaforma stessa (aumento del numero degli acceleratori e dei processori), che iii) di programmabilità. La tesi propone delle soluzioni a tutti e tre i problemi. Il linguaggio di programmazione usato è OpenMP, sia per la sua grande espressività a livello semantico, sia perché è lo standard de-facto per programmare sistemi a memoria condivisa

A novel access pattern-based multi-core memory architecture

Increasingly High-Performance Computing (HPC) applications run on heterogeneous multi-core platforms. The basic reason of the growing popularity of these architectures is their low power consumption, and high throughput oriented nature. However, this throughput imposes a requirement on the data to be supplied in a high throughput manner for the multi-core system. This results in the necessity of an efficient management of on-chip and off-chip memory data transfers, which is a significant challenge. Complex regular and irregular memory data transfer patterns are becoming widely dominant for a range of application domains including the scientific, image and signal processing. Data accesses can be arranged in independent patterns that an efficient memory management can exploit. The software based approaches using general purpose caches and on-chip memories are beneficial to some extent. However, the task of efficient data management for the throughput oriented devices could be improved by providing hardware mechanisms that exploit the knowledge of access patterns in memory management and scheduling of accesses for a heterogeneous multi-core architecture. The focus of this thesis is to present architectural explorations for a novel access pattern-based multi-core memory architecture. In general, the thesis covers four main aspects of memory system in this research. These aspects can be categorized as: i) Uni-core Memory System for Regular Data Pattern. ii) Multi-core Memory System for Regular Data Pattern. iii) Uni-core Memory System for Irregular Data Pattern. and iv) Multi-core Memory System for Irregular Data Pattern.Les aplicacions de computació d'alt rendiment (HPC) s'executen cada vegada més en plataformes heterogènies de múltiples nuclis. El motiu bàsic de la creixent popularitat d'aquestes arquitectures és el seu baix consum i la seva natura orientada a alt throughput. No obstant, aquest thoughput imposa el requeriment de que les dades es proporcionin al sistema també amb alt throughput. Això resulta en la necessitat de gestionar eficientment les trasferències de memòria (dins i fora del chip), un repte significatiu. Els patrons de transferències de memòria regulars però complexos així com els irregulars són cada vegada més dominants per a diversos dominis d'aplicacions, incloent el científic i el processat d'imagte i senyals. Aquests accessos a dades poden ser organitzats en patrons independents que un gestor de memòria eficient pot explotar. Els mètodes basats en programari emprant memòries cau de propòsit general i memòries al chip són beneficioses fins a cert punt. No obstant, la tasca de gestionar eficientment les transferències de dades per a dispositius orientats a throughput pot ser millorada oferint mecanismes hardware que explotin el coneixement dels patrons d'accés de les aplicacions, així com la planificació dels accessos a una arquitectura de múltiples nuclis. Aquesta tesis està enfocada a explorar una arquitectura de memòria novedosa per a processadors de múltiples nuclis, basada en els patrons d'accés. En general, la recerca de la tesis cobreix quatres aspectes principals del sistema de memòria. Aquests aspectes són: i) sistema de memòria per a un únic nucli amb patrons regulars, ii) sistema de memòria per a múltiples nuclis amb patrons regulars, iii) sistema de memòria per a un únic nucli amb patrons irregulars, iv) sistema de memòria per a múltiples nuclis amb patrons irregulars

SYSTEM-ON-A-CHIP (SOC)-BASED HARDWARE ACCELERATION FOR HUMAN ACTION RECOGNITION WITH CORE COMPONENTS

Today, the implementation of machine vision algorithms on embedded platforms or in portable systems is growing rapidly due to the demand for machine vision in daily human life. Among the applications of machine vision, human action and activity recognition has become an active research area, and market demand for providing integrated smart security systems is growing rapidly. Among the available approaches, embedded vision is in the top tier; however, current embedded platforms may not be able to fully exploit the potential performance of machine vision algorithms, especially in terms of low power consumption. Complex algorithms can impose immense computation and communication demands, especially action recognition algorithms, which require various stages of preprocessing, processing and machine learning blocks that need to operate concurrently. The market demands embedded platforms that operate with a power consumption of only a few watts. Attempts have been mad to improve the performance of traditional embedded approaches by adding more powerful processors; this solution may solve the computation problem but increases the power consumption. System-on-a-chip eld-programmable gate arrays (SoC-FPGAs) have emerged as a major architecture approach for improving power eciency while increasing computational performance. In a SoC-FPGA, an embedded processor and an FPGA serving as an accelerator are fabricated in the same die to simultaneously improve power consumption and performance. Still, current SoC-FPGA-based vision implementations either shy away from supporting complex and adaptive vision algorithms or operate at very limited resolutions due to the immense communication and computation demands. The aim of this research is to develop a SoC-based hardware acceleration workflow for the realization of advanced vision algorithms. Hardware acceleration can improve performance for highly complex mathematical calculations or repeated functions. The performance of a SoC system can thus be improved by using hardware acceleration method to accelerate the element that incurs the highest performance overhead. The outcome of this research could be used for the implementation of various vision algorithms, such as face recognition, object detection or object tracking, on embedded platforms. The contributions of SoC-based hardware acceleration for hardware-software codesign platforms include the following: (1) development of frameworks for complex human action recognition in both 2D and 3D; (2) realization of a framework with four main implemented IPs, namely, foreground and background subtraction (foreground probability), human detection, 2D/3D point-of-interest detection and feature extraction, and OS-ELM as a machine learning algorithm for action identication; (3) use of an FPGA-based hardware acceleration method to resolve system bottlenecks and improve system performance; and (4) measurement and analysis of system specications, such as the acceleration factor, power consumption, and resource utilization. Experimental results show that the proposed SoC-based hardware acceleration approach provides better performance in terms of the acceleration factor, resource utilization and power consumption among all recent works. In addition, a comparison of the accuracy of the framework that runs on the proposed embedded platform (SoCFPGA) with the accuracy of other PC-based frameworks shows that the proposed approach outperforms most other approaches

A High Speed Networked Signal Processing Platform for Multi-element Radio Telescopes

A new architecture is presented for a Networked Signal Processing System (NSPS) suitable for handling the real-time signal processing of multi-element radio telescopes. In this system, a multi-element radio telescope is viewed as an application of a multi-sensor, data fusion problem which can be decomposed into a general set of computing and network components for which a practical and scalable architecture is enabled by current technology. The need for such a system arose in the context of an ongoing program for reconfiguring the Ooty Radio Telescope (ORT) as a programmable 264-element array, which will enable several new observing capabilities for large scale surveys on this mature telescope. For this application, it is necessary to manage, route and combine large volumes of data whose real-time collation requires large I/O bandwidths to be sustained. Since these are general requirements of many multi-sensor fusion applications, we first describe the basic architecture of the NSPS in terms of a Fusion Tree before elaborating on its application for the ORT. The paper addresses issues relating to high speed distributed data acquisition, Field Programmable Gate Array (FPGA) based peer-to-peer networks supporting significant on-the fly processing while routing, and providing a last mile interface to a typical commodity network like Gigabit Ethernet. The system is fundamentally a pair of two co-operative networks, among which one is part of a commodity high performance computer cluster and the other is based on Commercial-Off The-Shelf (COTS) technology with support from software/firmware components in the public domain.Comment: 19 pages, 4 eps figures, To be published in Experimental Astronomy (Springer

A Dynamically Reconfigurable Parallel Processing Framework with Application to High-Performance Video Processing

Digital video processing demands have and will continue to grow at unprecedented rates. Growth comes from ever increasing volume of data, demand for higher resolution, higher frame rates, and the need for high capacity communications. Moreover, economic realities force continued reductions in size, weight and power requirements. The ever-changing needs and complexities associated with effective video processing systems leads to the consideration of dynamically reconfigurable systems. The goal of this dissertation research was to develop and demonstrate the viability of integrated parallel processing system that effectively and efficiently apply pre-optimized hardware cores for processing video streamed data. Digital video is decomposed into packets which are then distributed over a group of parallel video processing cores. Real time processing requires an effective task scheduler that distributes video packets efficiently to any of the reconfigurable distributed processing nodes across the framework, with the nodes running on FPGA reconfigurable logic in an inherently Virtual\u27 mode. The developed framework, coupled with the use of hardware techniques for dynamic processing optimization achieves an optimal cost/power/performance realization for video processing applications. The system is evaluated by testing processor utilization relative to I/O bandwidth and algorithm latency using a separable 2-D FIR filtering system, and a dynamic pixel processor. For these applications, the system can achieve performance of hundreds of 640x480 video frames per second across an eight lane Gen I PCIe bus. Overall, optimal performance is achieved in the sense that video data is processed at the maximum possible rate that can be streamed through the processing cores. This performance, coupled with inherent ability to dynamically add new algorithms to the described dynamically reconfigurable distributed processing framework, creates new opportunities for realizable and economic hardware virtualization.\u2

Lock-Based cache coherence protocol for chip multiprocessors

Chip multiprocessor (CMP) is replacing the superscalar processor due to its huge performance gains in terms of processor speed, scalability, power consumption and economical design. Since the CMP consists of multiple processor cores on a single chip usually with share cache resources, process synchronization is an important issue that needs to be dealt with. Synchronization is usually done by the operating system in case of shared memory multiprocessors (SMP). This work studies the effect of performing synchronization by the hardware through its integration with the cache coherence protocol. A novel cache coherence protocol, called Lock-based Cache Coherence Protocol (LCCP) was designed and its performance was compared with MESI cache coherence protocol. Experiments were performed by a functional multiprocessor simulator, MP_Simplesim, that was modified to do this work. A novel interconnection network was also designed and tested in terms of performance against the traditional bus approach by means of simulation