White-box methodologies, programming abstractions and libraries

EXCESS deliverable D2.2. More information at http://www.excess-project.eu/This deliverable reports the results of white-box methodologies and early results ofthe first prototype of libraries and programming abstractions as available by projectmonth 18 by Work Package 2 (WP2). It reports i) the latest results of Task 2.2on white-box methodologies, programming abstractions and libraries for developingenergy-efficient data structures and algorithms and ii) the improved results of Task2.1 on investigating and modeling the trade-off between energy and performance ofconcurrent data structures and algorithms. The work has been conducted on two mainEXCESS platforms: Intel platforms with recent Intel multicore CPUs and MovidiusMyriad1 platform

Models for energy consumption of data structures and algorithms

EXCESS deliverable D2.1. More information at http://www.excess-project.eu/This deliverable reports our early energy models for data structures and algorithms based on both micro-benchmarks and concurrent algorithms. It reports the early results of Task 2.1 on investigating and modeling the trade-off between energy and performance in concurrent data structures and algorithms, which forms the basis for the whole work package 2 (WP2). The work has been conducted on the two main EXCESS platforms: (1) Intel platform with recent Intel multi-core CPUs and (2) Movidius embedded platform

Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms

EXCESS deliverable D2.3. More information at http://www.excess-project.eu/This deliverable reports the results of the power models, energy models and librariesfor energy-efficient concurrent data structures and algorithms as available by projectmonth 30 of Work Package 2 (WP2). It reports i) the latest results of Task 2.2-2.4 onproviding programming abstractions and libraries for developing energy-efficient datastructures and algorithms and ii) the improved results of Task 2.1 on investigating andmodeling the trade-off between energy and performance of concurrent data structuresand algorithms. The work has been conducted on two main EXCESS platforms: Intelplatforms with recent Intel multicore CPUs and Movidius Myriad platforms

Modeling Energy Consumption of Computing Systems: from Homogeneous to Heterogeneous Systems

Nowadays, reducing energy consumption and improving the energy efficiency of computing systems become ones of the leading research topics in computer science. In order to improve energy efficiency, it is crucial to understand how computing systems consume energy. Power and energy models provide prediction and insight into how computing systems consume power and energy. However, it is challenging to build accurate power and energy models that can be used for general devices and general applications. In this thesis work, we propose three approaches of devising power and energy models, varying from homogeneous systems including one type of devices (e.g., CPU, GPU, ultra-low-power embedded system) to heterogeneous systems including several types of devices with different architectures. We developed new fine-grained power models supporting architecture-application co-design by considering both platform and application properties. The models were trained and validated with data from a set of micro-benchmarks and application kernels on Movidius Myriad, an ultra-low power embedded system. We also proposed and validated a framework predicting when to apply race-to-halt strategy to a given application. We devised ICE, a new energy complexity model for parallel (multi-threaded) algorithms that were validated on real multicore platforms and applicable to a wide range of parallel algorithms. The study also provided the platform parameters of the ICE models for eleven platforms including HPC, accelerator and embedded platforms to improve the model usability and accuracy. We proposed REOH, the holistic tuning approach to choose the most energy-efficient configurations for heterogeneous systems including several types of devices with different architectures (e.g., CPUs, GPUs). Based on the REOH approach, we developed an open-source energy-optimizing runtime framework for selecting an energy efficient configuration of a heterogeneous system for a given application at runtime

Identification and Analysis of Combined Quality Assurance Approaches

Context: Due to the increasing size and complexity of software today, the amount of effort for software quality assurance (QA) is growing and getting more and more expensive. There are many techniques lead to the improvement in software QA. Static analysis can obtain very good coverage while analyze program without execution, but it has the weakness of imprecision by false errors. In contrast, dynamic analysis can obtain only partial coverage due to a large number of possible test cases, but the reported errors are more precise. Static and dynamic analyses can complement each other by providing valuable information that would be missed by using isolated analysis technique. Although many studies investigate the QA approaches that combine static and dynamic QA techniques, it is unclear what we have learned from these studies, because no systematic synthesis exists to date. Method: This thesis is intended to provide basic key concepts for combined QA approaches. A major part of this thesis presents the systematic review that brings details discussion about state of the art on the approaches that combine static and dynamic QA techniques. The systematic review is aimed at the identification of the existed combined QA approaches, how to classify them, their purposes and input as well as introduce which combination is available. Result: The results show that, there are two relations in the combination of static and dynamic techniques such as integration and separation. Besides, the objectives of combined QA approaches were introduced according to QA process quality and product quality. The most common inputs for combined approaches were also discussed. Moreover, we identified which combination of static and dynamic techniques should or should not be used as well as the potential combination for further research

Identification and Analysis of Combined Quality Assurance Approaches

Context: Due to the increasing size and complexity of software today, the amount of effort for software quality assurance (QA) is growing and getting more and more expensive. There are many techniques lead to the improvement in software QA. Static analysis can obtain very good coverage while analyze program without execution, but it has the weakness of imprecision by false errors. In contrast, dynamic analysis can obtain only partial coverage due to a large number of possible test cases, but the reported errors are more precise. Static and dynamic analyses can complement each other by providing valuable information that would be missed by using isolated analysis technique. Although many studies investigate the QA approaches that combine static and dynamic QA techniques, it is unclear what we have learned from these studies, because no systematic synthesis exists to date. Method: This thesis is intended to provide basic key concepts for combined QA approaches. A major part of this thesis presents the systematic review that brings details discussion about state of the art on the approaches that combine static and dynamic QA techniques. The systematic review is aimed at the identification of the existed combined QA approaches, how to classify them, their purposes and input as well as introduce which combination is available. Result: The results show that, there are two relations in the combination of static and dynamic techniques such as integration and separation. Besides, the objectives of combined QA approaches were introduced according to QA process quality and product quality. The most common inputs for combined approaches were also discussed. Moreover, we identified which combination of static and dynamic techniques should or should not be used as well as the potential combination for further research