Composable local memory organisation for streaming applications on embedded MPSoCs

Multi-Processor Systems on a Chip (MPSoCs) are suitable platforms for the implementation of complex embedded applications. An MPSoC is composable if the functional and temporal behaviour of each application is independent of the absence or presence of other applications. Composability is required for application design and analysis in isolation, and integration with linear effort. In this paper we propose a composable organisation for the top level of a memory hierarchy. This organisation preserves the short (one cycle) access time desirable for a processor's frequent local accesses and enables the predictability demanded by real-time applications. We partition the local memory in two blocks, one private, for local tile data, and another shared for inter-tile data communication. To avoid application interference, we instantiate one such shared local memory block and an Remote Direct Memory Access (RDMA) for each application running on the processor. We implement this organisation on an MPSoC with two processors on an FPGA. On this platform we execute a composition of applications consisting of a JPEG decoder, and a synthetic application. Our experiments indicate that an application's timing is not affected by the behaviour of another application, thus composability is achieved. Moreover, the utilisation of the RDMA component leads to 45% performance increase on average for a number of workloads covering a large range of communication/computation ratios

Optimisation des mémoires dans le flot de conception des systèmes multiprocesseurs sur puces pour des applications de type multimédia

RÉSUMÉ Les systèmes multiprocesseurs sur puce (MPSoC) constituent l'un des principaux moteurs de la révolution industrielle des semi-conducteurs. Les MPSoCs jouissent d’une popularité grandissante dans le domaine des systèmes embarqués. Leur grande capacité de parallélisation à un très haut niveau d'intégration, en font de bons candidats pour les systèmes et les applications telles que les applications multimédia. La consommation d’énergie, la capacité de calcul et l’espace de conception sont les éléments dont dépendent les performances de ce type d’applications. La mémoire est le facteur clé permettant d’améliorer de façon substantielle leurs performances. Avec l’arrivée des applications multimédias embarquées dans l’industrie, le problème des gains de performances est vital. La masse de données traitées par ces applications requiert une grande capacité de calcul et de mémoire. Dernièrement, de nouveaux modèles de programmation ont fait leur apparition. Ces modèles offrent une programmation de plus haut niveau pour répondre aux besoins croissants des MPSoCs, d’où la nécessité de nouvelles approches d'optimisation et de placement pour les systèmes embarqués et leurs modèles de programmation. La conception niveau système des architectures MPSoCs pour les applications de type multimédia constitue un véritable défi technique. L’objectif général de cette thèse est de relever ce défi en trouvant des solutions. Plus spécifiquement, cette thèse se propose d’introduire le concept d’optimisation mémoire dans le flot de conception niveau système et d’observer leur impact sur différents modèles de programmation utilisés lors de la conception de MPSoCs. Il s’agit, autrement dit, de réaliser l’unification du domaine de la compilation avec celui de la conception niveau système pour une meilleure conception globale. La contribution de cette thèse est de proposer de nouvelles approches pour les techniques d'optimisation mémoire pour la conception MPSoCs avec différents modèles de programmation. Nos travaux de recherche concernent l'intégration des techniques d’optimisation mémoire dans le flot de conception de MPSoCs pour différents types de modèle de programmation. Ces travaux ont été exécutés en collaboration avec STMicroelectronics.----------ABSTRACT Multiprocessor systems-on-chip (MPSoC) are defined as one of the main drivers of the industrial semiconductors revolution. MPSoCs are gaining popularity in the field of embedded systems. Pursuant to their great ability to parallelize at a very high integration level, they are good candidates for systems and applications such as multimedia. Memory is becoming a key player for significant improvements in these applications (i.e. power, performance and area). With the emergence of more embedded multimedia applications in the industry, this issue becomes increasingly vital. The large amount of data manipulated by these applications requires high-capacity calculation and memory. Lately, new programming models have been introduced. These programming models offer a higher programming level to answer the increasing needs of MPSoCs. This leads to the need of new optimization and mapping approaches suitable for embedded systems and their programming models. The overall objective of this research is to find solutions to the challenges of system level design of applications such as multimedia. This entails the development of new approaches and new optimization techniques. The specific objective of this research is to introduce the concept of memory optimization in the system level conception flow and study its impact on different programming models used for MPSoCs’ design. In other words, it is the unification of the compilation and system level design domains. The contribution of this research is to propose new approaches for memory optimization techniques for MPSoCs’ design in different programming models. This thesis relates to the integration of memory optimization to varying programming model types in the MPSoCs conception flow. Our research was done in collaboration with STMicroelectronics

Towards Efficient Resource Allocation for Embedded Systems

Das Hauptthema ist die dynamische Ressourcenverwaltung in eingebetteten Systemen, insbesondere die Verwaltung von Rechenzeit und Netzwerkverkehr auf einem MPSoC. Die Idee besteht darin, eine Pipeline für die Verarbeitung von Mobiler Kommunikation auf dem Chip dynamisch zu schedulen, um die Effizienz der Hardwareressourcen zu verbessern, ohne den Ressourcenverbrauch des dynamischen Schedulings dramatisch zu erhöhen. Sowohl Software- als auch Hardwaremodule werden auf Hotspots im Ressourcenverbrauch untersucht und optimiert, um diese zu entfernen. Da Applikationen im Bereich der Signalverarbeitung normalerweise mit Hilfe von SDF-Diagrammen beschrieben werden können, wird deren dynamisches Scheduling optimiert, um den Ressourcenverbrauch gegenüber dem üblicherweise verwendeten statischen Scheduling zu verbessern. Es wird ein hybrider dynamischer Scheduler vorgestellt, der die Vorteile von Processing-Networks und der Planung von Task-Graphen kombiniert. Es ermöglicht dem Scheduler, ein Gleichgewicht zwischen der Parallelisierung der Berechnung und der Zunahme des dynamischen Scheduling-Aufands optimal abzuwägen. Der resultierende dynamisch erstellte Schedule reduziert den Ressourcenverbrauch um etwa 50%, wobei die Laufzeit im Vergleich zu einem statischen Schedule nur um 20% erhöht wird. Zusätzlich wird ein verteilter dynamischer SDF-Scheduler vorgeschlagen, der das Scheduling in verschiedene Teile zerlegt, die dann zu einer Pipeline verbunden werden, um mehrere parallele Prozessoren einzubeziehen. Jeder Scheduling-Teil wird zu einem Cluster mit Load-Balancing erweitert, um die Anzahl der parallel laufenden Scheduling-Jobs weiter zu erhöhen. Auf diese Weise wird dem vorhandene Engpass bei dem dynamischen Scheduling eines zentralisierten Schedulers entgegengewirkt, sodass 7x mehr Prozessoren mit dem Pipelined-Clustered-Dynamic-Scheduler für eine typische Signalverarbeitungsanwendung verwendet werden können. Das neue dynamische Scheduling-System setzt das Vorhandensein von drei verschiedenen Kommunikationsmodi zwischen den Verarbeitungskernen voraus. Bei der Emulation auf Basis des häufig verwendeten RDMA-Protokolls treten Leistungsprobleme auf. Sehr gut kann RDMA für einmalige Punkt-zu-Punkt-Datenübertragungen verwendet werden, wie sie bei der Ausführung von Task-Graphen verwendet werden. Process-Networks verwenden normalerweise Datenströme mit hohem Volumen und hoher Bandbreite. Es wird eine FIFO-basierte Kommunikationslösung vorgestellt, die einen zyklischen Puffer sowohl im Sender als auch im Empfänger implementiert, um diesen Bedarf zu decken. Die Pufferbehandlung und die Datenübertragung zwischen ihnen erfolgen ausschließlich in Hardware, um den Software-Overhead aus der Anwendung zu entfernen. Die Implementierung verbessert die Zugriffsverwaltung mehrerer Nutzer auf flächen-effiziente Single-Port Speichermodule. Es werden 0,8 der theoretisch möglichen Bandbreite, die normalerweise nur mit flächenmäßig teureren Dual-Port-Speichern erreicht wird. Der dritte Kommunikationsmodus definiert eine einfache Message-Passing-Implementierung, die ohne einen Verbindungszustand auskommt. Dieser Modus wird für eine effiziente prozessübergreifende Kommunikation des verteilten Scheduling-Systems und der engen Ansteuerung der restlichen Prozessoren benötigt. Eine Flusskontrolle in Hardware stellt sicher, dass eine große Anzahl von Sendern Nachrichten an denselben Empfänger senden kann. Dabei wird garantiert, dass alle Nachrichten korrekt empfangen werden, ohne dass eine Verbindung hergestellt werden muss und die Nachrichtenlaufzeit gering bleibt. Die Arbeit konzentriert sich auf die Optimierung des Codesigns von Hardware und Software, um die kompromisslose Ressourceneffizienz der dynamischen SDF-Graphen-Planung zu erhöhen. Besonderes Augenmerk wird auf die Abhängigkeiten zwischen den Ebenen eines verteilten Scheduling-Systems gelegt, das auf der Verfügbarkeit spezifischer hardwarebeschleunigter Kommunikationsmethoden beruht.:1 Introduction 1.1 Motivation 1.2 The Multiprocessor System on Chip Architecture 1.3 Concrete MPSoC Architecture 1.4 Representing LTE/5G baseband processing as Static Data Flow 1.5 Compuation Stack 1.6 Performance Hotspots Addressed 1.7 State of the Art 1.8 Overview of the Work 2 Hybrid SDF Execution 2.1 Addressed Performance Hotspot 2.2 State of the Art 2.3 Static Data Flow Graphs 2.4 Runtime Environment 2.5 Overhead of Deloying Tasks to a MPSoC 2.6 Interpretation of SDF Graphs as Task Graphs 2.7 Interpreting SDF Graphs as Process Networks 2.8 Hybrid Interpretation 2.9 Graph Topology Considerations 2.10 Theoretic Impact of Hybrid Interpretation 2.11 Simulating Hybrid Execution 2.12 Pipeline SDF Graph Example 2.13 Random SDF Graphs 2.14 LTE-like SDF Graph 2.15 Key Lernings 3 Distribution of Management 3.1 Addressed Performance Hotspot 3.2 State of the Art 3.3 Revising Deployment Overhead 3.4 Distribution of Overhead 3.5 Impact of Management Distribution to Resource Utilization 3.6 Reconfigurability 3.7 Key Lernings 4 Sliced FIFO Hardware 4.1 Addressed Performance Hotspot 4.2 State of the Art 4.3 System Environment 4.4 Sliced Windowed FIFO buffer 4.5 Single FIFO Evaluation 4.6 Multiple FIFO Evalutaion 4.7 Hardware Implementation 4.8 Key Lernings 5 Message Passing Hardware 5.1 Addressed Performance Hotspot 5.2 State of the Art 5.3 Message Passing Regarded as Queueing 5.4 A Remote Direct Memory Access Based Implementation 5.5 Hardware Implementation Concept 5.6 Evalutation of Performance 5.7 Key Lernings 6 SummaryThe main topic is the dynamic resource allocation in embedded systems, especially the allocation of computing time and network traffic on an multi processor system on chip (MPSoC). The idea is to dynamically schedule a mobile communication signal processing pipeline on the chip to improve hardware resource efficiency while not dramatically improve resource consumption because of dynamic scheduling overhead. Both software and hardware modules are examined for resource consumption hotspots and optimized to remove them. Since signal processing can usually be described with the help of static data flow (SDF) graphs, the dynamic handling of those is optimized to improve resource consumption over the commonly used static scheduling approach. A hybrid dynamic scheduler is presented that combines benefits from both processing networks and task graph scheduling. It allows the scheduler to optimally balance parallelization of computation and addition of dynamic scheduling overhead. The resulting dynamically created schedule reduces resource consumption by about 50%, with a runtime increase of only 20% compared to a static schedule. Additionally, a distributed dynamic SDF scheduler is proposed that splits the scheduling into different parts, which are then connected to a scheduling pipeli ne to incorporate multiple parallel working processors. Each scheduling stage is reworked into a load-balanced cluster to increase the number of parallel scheduling jobs further. This way, the still existing dynamic scheduling bottleneck of a centralized scheduler is widened, allowing handling 7x more processors with the pipelined, clustered dynamic scheduler for a typical signal processing application. The presented dynamic scheduling system assumes the presence of three different communication modes between the processing cores. When emulated on top of the commonly used remote direct memory access (RDMA) protocol, performance issues are encountered. Firstly, RDMA can neatly be used for single-shot point-to-point data transfers, like used in task graph scheduling. Process networks usually make use of high-volume and high-bandwidth data streams. A first in first out (FIFO) communication solution is presented that implements a cyclic buffer on both sender and receiver to serve this need. The buffer handling and data transfer between them are done purely in hardware to remove software overhead from the application. The implementation improves the multi-user access to area-efficient single port on-chip memory modules. It achieves 0.8 of the theoretically possible bandwidth, usually only achieved with area expensive dual-port memories. The third communication mode defines a lightweight message passing (MP) implementation that is truly connectionless. It is needed for efficient inter-process communication of the distributed and clustered scheduling system and the worker processing units’ tight coupling. A hardware flow control assures that an arbitrary number of senders can spontaneously start sending messages to the same receiver. Yet, all messages are guaranteed to be correctly received while eliminating the need for connection establishment and keeping a low message delay. The work focuses on the hardware-software codesign optimization to increase the uncompromised resource efficiency of dynamic SDF graph scheduling. Special attention is paid to the inter-level dependencies in developing a distributed scheduling system, which relies on the availability of specific hardwareaccelerated communication methods.:1 Introduction 1.1 Motivation 1.2 The Multiprocessor System on Chip Architecture 1.3 Concrete MPSoC Architecture 1.4 Representing LTE/5G baseband processing as Static Data Flow 1.5 Compuation Stack 1.6 Performance Hotspots Addressed 1.7 State of the Art 1.8 Overview of the Work 2 Hybrid SDF Execution 2.1 Addressed Performance Hotspot 2.2 State of the Art 2.3 Static Data Flow Graphs 2.4 Runtime Environment 2.5 Overhead of Deloying Tasks to a MPSoC 2.6 Interpretation of SDF Graphs as Task Graphs 2.7 Interpreting SDF Graphs as Process Networks 2.8 Hybrid Interpretation 2.9 Graph Topology Considerations 2.10 Theoretic Impact of Hybrid Interpretation 2.11 Simulating Hybrid Execution 2.12 Pipeline SDF Graph Example 2.13 Random SDF Graphs 2.14 LTE-like SDF Graph 2.15 Key Lernings 3 Distribution of Management 3.1 Addressed Performance Hotspot 3.2 State of the Art 3.3 Revising Deployment Overhead 3.4 Distribution of Overhead 3.5 Impact of Management Distribution to Resource Utilization 3.6 Reconfigurability 3.7 Key Lernings 4 Sliced FIFO Hardware 4.1 Addressed Performance Hotspot 4.2 State of the Art 4.3 System Environment 4.4 Sliced Windowed FIFO buffer 4.5 Single FIFO Evaluation 4.6 Multiple FIFO Evalutaion 4.7 Hardware Implementation 4.8 Key Lernings 5 Message Passing Hardware 5.1 Addressed Performance Hotspot 5.2 State of the Art 5.3 Message Passing Regarded as Queueing 5.4 A Remote Direct Memory Access Based Implementation 5.5 Hardware Implementation Concept 5.6 Evalutation of Performance 5.7 Key Lernings 6 Summar

Green computing: power optimisation of VFI-based real-time multiprocessor dataflow applications (extended version)

Execution time is no longer the only performance metric for computer systems. In fact, a trend is emerging to trade raw performance for energy savings. Techniques like Dynamic Power Management (DPM, switching to low power state) and Dynamic Voltage and Frequency Scaling (DVFS, throttling processor frequency) help modern systems to reduce their power consumption while adhering to performance requirements. To balance flexibility and design complexity, the concept of Voltage and Frequency Islands (VFIs) was recently introduced for power optimisation. It achieves fine-grained system-level power management, by operating all processors in the same VFI at a common frequency/voltage.This paper presents a novel approach to compute a power management strategy combining DPM and DVFS. In our approach, applications (modelled in full synchronous dataflow, SDF) are mapped on heterogeneous multiprocessor platforms (partitioned in voltage and frequency islands). We compute an energy-optimal schedule, meeting minimal throughput requirements. We demonstrate that the combination of DPM and DVFS provides an energy reduction beyond considering DVFS or DMP separately. Moreover, we show that by clustering processors in VFIs, DPM can be combined with any granularity of DVFS. Our approach uses model checking, by encoding the optimisation problem as a query over priced timed automata. The model-checker Uppaal Cora extracts a cost minimal trace, representing a power minimal schedule. We illustrate our approach with several case studies on commercially available hardware

Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Programming models for many-core architectures: a co-design approach

Common many-core processors contain tens of cores and distributed memory. Compared to a multicore system, which only has a few tightly coupled cores sharing a single bus and memory, several complex problems arise. Notably, many cores require many parallel tasks to fully utilize the cores, and communication happens in a distributed and decentralized way. Therefore, programming such a processor requires the application to exhibit concurrency. In contrast to a single-core application, a concurrent application has to deal with memory state changes with an observable (non-deterministic) intermediate state. The complexity introduced by these problems makes programming a many-core system with a single-core-based programming approach notoriously hard.\ud \ud The central concept of this thesis is that abstractions, which are related to (many-core) programming, are structured in a single platform model. A platform is a layered view of the hardware, a memory model, a concurrency model, a model of computation, and compile-time and run-time tooling. Then, a programming model is a specific view on this platform, which is used by a programmer. In this view, some details can be hidden from the programmer's perspective, some details cannot. For example, an operating system presents an infinite number of parallel virtual execution units to the application whilst it hides details regarding scheduling. On the other hand, a programmer usually has balance workload among threads by hand.\ud \ud This thesis presents modifications to different abstraction layers of a many-core architecture, in order to make the system as a whole more efficient, and to reduce the programming complexity. These modifications influence other abstractions in the platform, and especially the programming model. Therefore, this thesis applies co-design on all models. Notably, co-design of the memory model, concurrency model, and model of computation is required for a scalable implementation of lambda-calculus. Moreover, only the combination of requirements of the many-core hardware from one side and the concurrency model from the other leads to a memory model abstraction. Hence, this thesis shows that to cope with the current trends in many-core architectures from a programming perspective, it is essential and feasible to inspect and adapt all abstractions collectively