Scratchpad Sharing in GPUs

GPGPU applications exploit on-chip scratchpad memory available in the Graphics Processing Units (GPUs) to improve performance. The amount of thread level parallelism present in the GPU is limited by the number of resident threads, which in turn depends on the availability of scratchpad memory in its streaming multiprocessor (SM). Since the scratchpad memory is allocated at thread block granularity, part of the memory may remain unutilized. In this paper, we propose architectural and compiler optimizations to improve the scratchpad utilization. Our approach, Scratchpad Sharing, addresses scratchpad under-utilization by launching additional thread blocks in each SM. These thread blocks use unutilized scratchpad and also share scratchpad with other resident blocks. To improve the performance of scratchpad sharing, we propose Owner Warp First (OWF) scheduling that schedules warps from the additional thread blocks effectively. The performance of this approach, however, is limited by the availability of the shared part of scratchpad. We propose compiler optimizations to improve the availability of shared scratchpad. We describe a scratchpad allocation scheme that helps in allocating scratchpad variables such that shared scratchpad is accessed for short duration. We introduce a new instruction, relssp, that when executed, releases the shared scratchpad. Finally, we describe an analysis for optimal placement of relssp instructions such that shared scratchpad is released as early as possible. We implemented the hardware changes using the GPGPU-Sim simulator and implemented the compiler optimizations in Ocelot framework. We evaluated the effectiveness of our approach on 19 kernels from 3 benchmarks suites: CUDA-SDK, GPGPU-Sim, and Rodinia. The kernels that underutilize scratchpad memory show an average improvement of 19% and maximum improvement of 92.17% compared to the baseline approach

An offshore wind union? Diversity and convergence in European offshore wind governance

Offshore wind megaprojects in European waters have significant carbon abatement potential and increasing their number is a policy goal for several European maritime nations. But experience has shown that governance of large-scale, commercial offshore wind development is not straightforward. It is found that in five EU Member States, policy innovation intended to enable investment in offshore wind projects is leading to a convergence upon a distinctive European model of offshore wind governance. Notably, the European Union appears to play a relatively small role in this process and further research into how offshore wind policy innovation propagates in the EU is warranted

Benthic monitoring and sampling design and effort to detect spatial changes: A case study using data from offshore wind farm sites

© 2015 Elsevier Ltd. All rights reserved. The exploitation of renewable energies, in particular offshore wind farms (OWFs), is an expanding sector which involves activities that may adversely affect the marine benthic ecology. Fit-for-purpose monitoring is required with sufficient statistical power to detect ecologically meaningful changes, but to date there have been no studies on the suitability of monitoring programmes applied to OWFs. The theoretical relationship of sampling effort with precision in community estimates and sensitivity of the analysis in detecting spatial changes was investigated, this latter assessed through power analysis. Benthic community monitoring strategies and descriptors applied to UK OWFs were used to interrogate real data variability in the marine environment. There was a general lack of clarity in the survey rationale and hypotheses tested within OWF monitoring programmes hence a lack of rigour in the survey design and statistical testing. Consequently the statistical properties of monitoring strategies have been rarely assessed. Precision of mean estimates of benthic community descriptors and the sensitivity in detecting differences in the means increased with sampling effort. At the average sampling effort applied in the OWF case studies (4 stations per impact type area and 3 replicates per station), the studies had sufficient power to detect a ≥50% change between areas in mean benthic species richness (S; 5 species). Due to their higher variability than S, more stations per impact type area were required to reliably detect a ≥50% change between areas in mean benthic abundance (N; 5 stations) and mean biomass (B; 10 stations). Higher sensitivity and precision of estimates of S, N and B was achieved with transformation of data. Understanding the general implications of monitoring design on the sensitivity of the detection of spatial changes is important, particularly when monitoring effort has to be adjusted due to logistic and financial constraints. Although there is no 'one-size-fits-all' approach to marine environmental data acquisition, this study guides researchers, developers and regulators in optimising benthic monitoring strategies at OWFs

The large scale impact of offshore wind farm structures on pelagic primary productivity in the southern North Sea

The increasing demand for renewable energy is projected to result in a 40-fold increase in offshore wind electricity in the European Union by 2030. Despite a great number of local impact studies for selected marine populations, the regional ecosystem impacts of offshore wind farm structures are not yet well assessed nor understood. Our study investigates whether the accumulation of epifauna, dominated by the filter feeder Mytilus edulis (blue mussel), on turbine structures affects pelagic primary productivity and ecosystem functioning in the southern North Sea. We estimate the anthropogenically increased potential distribution based on the current projections of turbine locations and reported patterns of M. edulis settlement. This distribution is integrated through the Modular Coupling System for Shelves and Coasts to state-of-the-art hydrodynamic and ecosystem models. Our simulations reveal non-negligible potential changes in regional annual primary productivity of up to 8% within the offshore wind farm area, and induced maximal increases of the same magnitude in daily productivity also far from the wind farms. Our setup and modular coupling are effective tools for system scale studies of other environmental changes arising from large-scale offshore wind-farming such as ocean physics and distributions of pelagic top predators.Comment: 17 pages, 6 figures, re-revised manuscript submitted to Hydrobiologi

Checking and Enforcing Security through Opacity in Healthcare Applications

The Internet of Things (IoT) is a paradigm that can tremendously revolutionize health care thus benefiting both hospitals, doctors and patients. In this context, protecting the IoT in health care against interference, including service attacks and malwares, is challenging. Opacity is a confidentiality property capturing a system's ability to keep a subset of its behavior hidden from passive observers. In this work, we seek to introduce an IoT-based heart attack detection system, that could be life-saving for patients without risking their need for privacy through the verification and enforcement of opacity. Our main contributions are the use of a tool to verify opacity in three of its forms, so as to detect privacy leaks in our system. Furthermore, we develop an efficient, Symbolic Observation Graph (SOG)-based algorithm for enforcing opacity