Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Power capping is a fundamental method for reducing the energy consumption of a wide range of modern computing environments, ranging from mobile embedded systems to datacentres. Unfortunately, maximising performance and system efficiency under static power caps remains challenging, while maximising performance under dynamic power caps has been largely unexplored. We present an adaptive power capping method that reduces the power consumption and maximizes the performance of heterogeneous SoCs for mobile and server platforms. Our technique combines power capping with coordinated DVFS, data partitioning and core allocations on a heterogeneous SoC with ARM processors and FPGA resources. We design our framework as a run-time system based on OpenMP and OpenCL to utilise the heterogeneous resources. We evaluate it through five data-parallel benchmarks on the Xilinx SoC which allows fully voltage and frequency control. Our experiments show a significant performance boost of 30% under dynamic power caps with concurrent execution on ARM and FPGA, compared to a naive separate approach.

Rapid Implementation and Optimisation of DSP Systems on FPGA-Centric Hetrogeneous Platforms

This paper, chosen as a best paper from the 2005 SAMOS Workshop on Computer Systems: describes the for the first time the major Abhainn project for automated system level design of embedded signal processing systems. In particular, this describes four key novelties: novel algorithm modelling techniques for DSP systems, automated implementation realisation, algorithm transformation for system optimisation and automated inter-processor communication. This is applied to two complex systems: a radar and sonar system. In both cases technology which allows non-experts to automatically create low-overhead, high performance embedded signal processing systems is exhibited.

Taking pluralism seriously:Embedded moralities in management accounting and control systems

Professor Norman Macintosh has long been a leading, and at times a dissonant, voice in critical accounting studies, exhibiting an intellectual dexterity seldom encountered in the accounting academy. His work ranges from the application of traditional organizational theories within work organizations to poststructural renderings of capital market exigencies. Here, we consider and extend Professor Macintosh's work contemplating the morality embedded within, and propagated by, management accounting and control systems (macs). We begin with Macintosh (1995) employing structuration theory in investigating the ethics of profit manipulation within large, decentralized corporations. The work highlights the fundamental dialectical contradictions within these work organizations, demonstrates the indeterminacy of traditional ethical reasoning, and shows the extent to which macs provide legitimating underpinnings for management action. We propose to extend the conversation using the tools provided in Macintosh's subsequent work: a Levinasian ethic (Macintosh et al., 2009), and heteroglossic accounting (Macintosh, 2002)—both emerging from his poststructuralist predilections. A Levinasian perspective provides an ontologically grounded ethic, and heteroglossic accounting calls for multiple accountings representing alternative moral voices. A critical dialogic framework is proposed as a theoretic for imagining heteroglossic accounting that takes pluralism seriously by recognizing the reality of irresolvable differences and asymmetric power relationships associated with assorted moral perspectives.

Software Release Planning: An Evolutionary and Iterative Approach

Abstract To achieve higher flexibility and to better satisfy actual customer requirements, there is an increasing tendency to develop and deliver software in an incremental fashion. In adopting this process, requirements are delivered in releases and so a decision has to be made on which requirements should be delivered in which release. Three main considerations that need to be taken account of are the technical precedences inherent in the requirements, the typically conflicting priorities as determined by the representative stakeholders, as well as the balance between required and available effort. The technical precedence constraints relate to situations where one requirement cannot be implemented until another is completed or where one requirement is implemented in the same increment as another one. Stakeholder preferences may be based on the perceived value or urgency of delivered requirements to the different stakeholders involved. The technical priorities and individual stakeholder priorities may be in conflict and difficult to reconcile. This paper provides (i) a method for optimally allocating requirements to increments; (ii) a means of assessing and optimizing the degree to which the ordering conflicts with stakeholder priorities within technical precedence constraints; (iii) a means of balancing required and available resources for all increments; and (iv) an overall method called EVOLVE aimed at the continuous planning of incremental software development. The optimization method used is iterative and essentially based on a genetic algorithm. A set of the most promising candidate solutions is generated to support the final decision. The paper evaluates the proposed approach using a sample project.