Branch and Bound Based Load Balancing for Parallel Applications

Abstract. Many parallel applications are highly dynamic in nature. In some, computation and communication patterns change gradually dur-ing the run; in others those characteristics change abruptly. Such dy-namic applications require an adaptive load balancing strategy. We are exploring an adaptive approach based on multi-partition object-based decomposition, supported by object migration. For many applications, relatively infrequent load balancing is needed. In these cases it becomes economical to spend considerable computation time toward arriving at a nearly optimal mapping of objects to processors. We present an optimal-seeking branch and bound based strategy that finds nearly optimal so-lutions to such load balancing problems quickly, and can continuously improve such solutions as time permits.

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Concurrency-based approaches to parallel programming

The inevitable transition to parallel programming can be facilitated by appropriate tools, including languages and libraries. After describing the needs of applications developers, this paper presents three specific approaches aimed at development of efficient and reusable parallel software for irregular and dynamic-structured problems. A salient feature of all three approaches in their exploitation of concurrency within a processor. Benefits of individual approaches such as these can be leveraged by an interoperability environment which permits modules written using different approaches to co-exist in single applications

A checkpoint/recovery model for heterogeneous dataflow computations using work-stealing

This paper presents a new checkpoint/recovery method for dataflow computations using work-stealing in heterogeneous environments as found in grid or cluster computing. Basing the state of the computation on a dynamic macro dataflow graph, it is shown that the mechanisms provide effective checkpointing for multithreaded applications in heterogeneous environments. Two methods, Systematic Event Logging and Theft-Induced Checkpointing, are presented that are efficient and extremely flexible under the system-state model, allowing for recovery on different platforms under different number of processors. A formal analysis of the overhead induced by both methods is presented, followed by an experimental evaluation in a large cluster. It is shown that both methods have very small overhead and that trade-offs between checkpointing and recovery cost can be controlled