READEX: Linking Two Ends of the Computing Continuum to Improve Energy-efficiency in Dynamic Applications

In both the embedded systems and High Performance Computing domains, energy-efficiency has become one of the main design criteria. Efficiently utilizing the resources provided in computing systems ranging from embedded systems to current petascale and future Exascale HPC systems will be a challenging task. Suboptimal designs can potentially cause large amounts of underutilized resources and wasted energy. In both domains, a promising potential for improving efficiency of scalable applications stems from the significant degree of dynamic behaviour, e.g., runtime alternation in application resource requirements and workloads. Manually detecting and leveraging this dynamism to improve performance and energy-efficiency is a tedious task that is commonly neglected by developers. However, using an automatic optimization approach, application dynamism can be analysed at design time and used to optimize system configurations at runtime. The European Union Horizon 2020 READEX (Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing) project will develop a tools-aided auto-tuning methodology inspired by the system scenario methodology used in embedded systems. Dynamic behaviour of HPC applications will be exploited to achieve improved energy-efficiency and performance. Driven by a consortium of European experts from academia, HPC resource providers, and industry, the READEX project aims at developing the first of its kind generic framework to split design time and runtime automatic tuning while targeting heterogeneous system at the Exascale level. This paper describes plans for the project as well as early results achieved during its first year. Furthermore, it is shown how project results will be brought back into the embedded systems domain

Auditing with incomplete logs

The protection of sensitive information is of utmost importance for organizations. The complexity and dynamism of modern businesses are forcing a re-think of traditional protection mechanisms. In particular, a priori policy enforcement mechanisms are often complemented with auditing mechanisms that rely on an a posteriori analysis of logs recording users’ activities to prove conformity to policies and detect policy violations when a valid explanation of conformity does not exist. However, existing auditing solutions require that the information necessary to assess policy compliance is available for the analysis. This assumption is not realistic. Indeed, a good deal of users’ activities may not be under the control of the IT system and thus they cannot be logged. In this paper we tackle the problem of accessing policy compliance in presence of incomplete logs. In particular, we present an auditing framework to assist analysts in finding a valid explanation for the events recorded in the logs and to pinpoint policy violations if such an explanation does not exist, when logs are incomplete. We also introduce two strategies for the refinement of plausible explanations of conformity to drive analysts along the auditing process. Our framework has been implemented on top of CIFF, an abductive proof procedure, and the efficiency and effectiveness of the refinement strategies evaluated. Keywords: Abduction, Policy Compliance, Abductive Reasonin

The READEX formalism for automatic tuning for energy efficiency

Energy efficiency is an important aspect of future exascale systems, mainly due to rising energy cost. Although High performance computing (HPC) applications are compute centric, they still exhibit varying computational characteristics in different regions of the program, such as compute-, memory-, and I/O-bound code regions. Some of today’s clusters already offer mechanisms to adjust the system to the resource requirements of an application, e.g., by controlling the CPU frequency. However, manually tuning for improved energy efficiency is a tedious and painstaking task that is often neglected by application developers. The European Union’s Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing) aims at developing a tools-aided approach for improved energy efficiency of current and future HPC applications. To reach this goal, the READEX project combines technologies from two ends of the compute spectrum, embedded systems and HPC, constituting a split design-time/runtime methodology. From the HPC domain, the Periscope Tuning Framework (PTF) is extended to perform dynamic auto-tuning of fine-grained application regions using the systems scenario methodology, which was originally developed for improving the energy efficiency in embedded systems. This paper introduces the concepts of the READEX project, its envisioned implementation, and preliminary results that demonstrate the feasibility of this approach