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This paper presents a new approach for mapping task graphs to heterogeneous hardware/software computing systems using heuristic search techniques. Two techniques: (1) integration of clustering, mapping, and scheduling in a single step and (2) multiple neighborhood functions strategy are proposed to enhance quality of mapping/scheduling solutions. Our approach is demonstrated by case studies involving 40 randomly generated task graphs, as well as four real applications including signal processing and pattern recognition. Experimental results show that the proposed integrated approach outperforms a separate approach in terms of quality of the mapping/scheduling solution by up to 18.3% for a heterogeneous system which includes a microprocessor, a floating-point digital signal processor, and an FPGA.

This paper describes a strategy that integrates the task mapping and task scheduling steps for heuristic search techniques, with multiple neighbourhood functions to reduce search time and enchance solution quality in developing heterogeneous computing systems. For case studies involving 40 randomly generated task graphs and the fast Fourier transform, experimental results show that our approach outperfroms previous approaches in terms of search time by up to 93 times, and solution quality by up to 22.6% for a system with a microprocessor, a floating-point digital signal processor, and an FPGA.

A technique for parallelising multiple loops in a heterogeneous computing system is presented. Loops are first unrolled and then broken up into multiple tasks which are mapped to reconfigurable hardware. A performance-driven optimisation is applied to find the best unrolling factor for each loop under hardware size constraints. The approach is demonstrated using three applications: speech recognition, image processing, and the N-Body problem. Experimental results show that a maximum speedup of 34 is achieved on a 274 MHz FPGA for the N-Body over a 2.6 GHz microprocessor, which is 4.1 times higher than that of an approach without unrolling.

Concentrations and percent loadings of pharmaceutically active compounds (PhACs) and other emerging contaminants released from healthcare facilities (2 hospitals and a long-term care facility) to a sewage treatment plant (STP) in a large urban sewershed were evaluated. An additional hospital outside the sewershed was also monitored. Fourteen of the 24 steroids/hormones and 88 of the 117 PhACs and emerging contaminants were detected at least once. Commonly used substances, including cotinine, caffeine and its metabolite 1,7-dimethylxanthine, ibuprofen and naproxen (analgesics), venlafaxine (antidepressant), and N,N-diethyl-meta-toluamide (insect repellant), were detected in all samples at all sites. Concentrations detected in the large specialty hospital outside the sewershed were similar to those within the sewershed. Cytotoxic drugs (tamoxifen and cyclophosphamide) and x-ray contrast media (iopamidol and diatrizoic acid) were infrequently detected in hospital effluents. Analysis for antibiotics indicated that azithromycin, clarithromycin, ciprofloxacin, erythromycin, ofloxacin, and sulfamethoxazole were consistently detected in hospital wastewaters, as was triclosan (antibacterial agent). Fifteen compounds individually contributed greater than 1% to the total PhAC and emerging contaminant load to the STP from the 2 hospitals in the sewershed, and 9 compounds in the STP effluent exceeded ecotoxicological criteria. The present survey demonstrates that point source discharges from healthcare facilities in this sewershed make a small contribution to the overall PhAC and emerging contaminant loading compared with the total concentrations entering the receiving STP.