Embedded dynamic programming networks for networks-on-chip

PhD ThesisRelentless technology downscaling and recent technological advancements in three dimensional integrated circuit (3D-IC) provide a promising prospect to realize heterogeneous system-on-chip (SoC) and homogeneous chip multiprocessor (CMP) based on the networks-onchip (NoCs) paradigm with augmented scalability, modularity and performance. In many cases in such systems, scheduling and managing communication resources are the major design and implementation challenges instead of the computing resources. Past research efforts were mainly focused on complex design-time or simple heuristic run-time approaches to deal with the on-chip network resource management with only local or partial information about the network. This could yield poor communication resource utilizations and amortize the benefits of the emerging technologies and design methods. Thus, the provision for efficient run-time resource management in large-scale on-chip systems becomes critical. This thesis proposes a design methodology for a novel run-time resource management infrastructure that can be realized efficiently using a distributed architecture, which closely couples with the distributed NoC infrastructure. The proposed infrastructure exploits the global information and status of the network to optimize and manage the on-chip communication resources at run-time. There are four major contributions in this thesis. First, it presents a novel deadlock detection method that utilizes run-time transitive closure (TC) computation to discover the existence of deadlock-equivalence sets, which imply loops of requests in NoCs. This detection scheme, TC-network, guarantees the discovery of all true-deadlocks without false alarms in contrast to state-of-the-art approximation and heuristic approaches. Second, it investigates the advantages of implementing future on-chip systems using three dimensional (3D) integration and presents the design, fabrication and testing results of a TC-network implemented in a fully stacked three-layer 3D architecture using a through-silicon via (TSV) complementary metal-oxide semiconductor (CMOS) technology. Testing results demonstrate the effectiveness of such a TC-network for deadlock detection with minimal computational delay in a large-scale network. Third, it introduces an adaptive strategy to effectively diffuse heat throughout the three dimensional network-on-chip (3D-NoC) geometry. This strategy employs a dynamic programming technique to select and optimize the direction of data manoeuvre in NoC. It leads to a tool, which is based on the accurate HotSpot thermal model and SystemC cycle accurate model, to simulate the thermal system and evaluate the proposed approach. Fourth, it presents a new dynamic programming-based run-time thermal management (DPRTM) system, including reactive and proactive schemes, to effectively diffuse heat throughout NoC-based CMPs by routing packets through the coolest paths, when the temperature does not exceed chip’s thermal limit. When the thermal limit is exceeded, throttling is employed to mitigate heat in the chip and DPRTM changes its course to avoid throttled paths and to minimize the impact of throttling on chip performance. This thesis enables a new avenue to explore a novel run-time resource management infrastructure for NoCs, in which new methodologies and concepts are proposed to enhance the on-chip networks for future large-scale 3D integration.Iraqi Ministry of Higher Education and Scientific Research (MOHESR)

Resource Management Algorithms for Computing Hardware Design and Operations: From Circuits to Systems

The complexity of computation hardware has increased at an unprecedented rate for the last few decades. On the computer chip level, we have entered the era of multi/many-core processors made of billions of transistors. With transistor budget of this scale, many functions are integrated into a single chip. As such, chips today consist of many heterogeneous cores with intensive interaction among these cores. On the circuit level, with the end of Dennard scaling, continuously shrinking process technology has imposed a grand challenge on power density. The variation of circuit further exacerbated the problem by consuming a substantial time margin. On the system level, the rise of Warehouse Scale Computers and Data Centers have put resource management into new perspective. The ability of dynamically provision computation resource in these gigantic systems is crucial to their performance. In this thesis, three different resource management algorithms are discussed. The first algorithm assigns adaptivity resource to circuit blocks with a constraint on the overhead. The adaptivity improves resilience of the circuit to variation in a cost-effective way. The second algorithm manages the link bandwidth resource in application specific Networks-on-Chip. Quality-of-Service is guaranteed for time-critical traffic in the algorithm with an emphasis on power. The third algorithm manages the computation resource of the data center with precaution on the ill states of the system. Q-learning is employed to meet the dynamic nature of the system and Linear Temporal Logic is leveraged as a tool to describe temporal constraints. All three algorithms are evaluated by various experiments. The experimental results are compared to several previous work and show the advantage of our methods

On-Line Dependability Enhancement of Multiprocessor SoCs by Resource Management

This paper describes a new approach towards dependable design of homogeneous multi-processor SoCs in an example satellite-navigation application. First, the NoC dependability is functionally verified via embedded software. Then the Xentium processor tiles are periodically verified via on-line self-testing techniques, by using a new IIP Dependability Manager. Based on the Dependability Manager results, faulty tiles are electronically excluded and replaced by fault-free spare tiles via on-line resource management. This integrated approach enables fast electronic fault detection/diagnosis and repair, and hence a high system availability. The dependability application runs in parallel with the actual application, resulting in a very dependable system. All parts have been verified by simulation

Design of an Efficient Interconnection Network of Temperature Sensors

Temperature has become a first class design constraint because high temperatures adversely affect circuit reliability, static power and degrade the performance. In this scenario, thermal characterization of ICs and on-chip temperature monitoring represent fundamental tasks in electronic design. In this work, we analyze the features that an interconnection network of temperature sensors must fulfill. Departing from the network topology, we continue with the proposal of a very light-weight network architecture based on digitalization resource sharing. Our proposal supposes a 16% improvement in area and power consumption compared to traditional approache

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

A Survey of Prediction and Classification Techniques in Multicore Processor Systems

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems