Formal Modelling, Testing and Verification of HSA Memory Models using Event-B

The HSA Foundation has produced the HSA Platform System Architecture Specification that goes a long way towards addressing the need for a clear and consistent method for specifying weakly consistent memory. HSA is specified in a natural language which makes it open to multiple ambiguous interpretations and could render bugs in implementations of it in hardware and software. In this paper we present a formal model of HSA which can be used in the development and verification of both concurrent software applications as well as in the development and verification of the HSA-compliant platform itself. We use the Event-B language to build a provably correct hierarchy of models from the most abstract to a detailed refinement of HSA close to implementation level. Our memory models are general in that they represent an arbitrary number of masters, programs and instruction interleavings. We reason about such general models using refinements. Using Rodin tool we are able to model and verify an entire hierarchy of models using proofs to establish that each refinement is correct. We define an automated validation method that allows us to test baseline compliance of the model against a suite of published HSA litmus tests. Once we complete model validation we develop a coverage driven method to extract a richer set of tests from the Event-B model and a user specified coverage model. These tests are used for extensive regression testing of hardware and software systems. Our method of refinement based formal modelling, baseline compliance testing of the model and coverage driven test extraction using the single language of Event-B is a new way to address a key challenge facing the design and verification of multi-core systems.Comment: 9 pages, 10 figure

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Computing server power modeling in a data center: survey,taxonomy and performance evaluation

Data centers are large scale, energy-hungry infrastructure serving the increasing computational demands as the world is becoming more connected in smart cities. The emergence of advanced technologies such as cloud-based services, internet of things (IoT) and big data analytics has augmented the growth of global data centers, leading to high energy consumption. This upsurge in energy consumption of the data centers not only incurs the issue of surging high cost (operational and maintenance) but also has an adverse effect on the environment. Dynamic power management in a data center environment requires the cognizance of the correlation between the system and hardware level performance counters and the power consumption. Power consumption modeling exhibits this correlation and is crucial in designing energy-efficient optimization strategies based on resource utilization. Several works in power modeling are proposed and used in the literature. However, these power models have been evaluated using different benchmarking applications, power measurement techniques and error calculation formula on different machines. In this work, we present a taxonomy and evaluation of 24 software-based power models using a unified environment, benchmarking applications, power measurement technique and error formula, with the aim of achieving an objective comparison. We use different servers architectures to assess the impact of heterogeneity on the models' comparison. The performance analysis of these models is elaborated in the paper

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome