Principal Kernel Analysis: A Tractable Methodology to Simulate Scaled GPU Workloads

In this paper, cell loading and shipment method optimisation problem in a cellular manufacturing system are studied. A hierarchical methodology that consists of mathematical optimisation model, genetic algorithms (GAs) and artificial neural networks (ANNs) were proposed. The mathematical model is compared with the GA in terms of the optimisation performance. Next, ANN model was developed as decision support tool to study the impact of GA parameters on the solution quality. Several problem sizes were experimented with the proposed GA and the mathematical model, and compared. GA was run to make a total of 648 sample solutions for the 20-job problem. Next, ANN model was built based on the sample solutions' data and the optimal ANN model is identified out of 1,000 networks. The results were also coupled with sensitivity and statistical analyses, which indicated that type of crossover and mutation operators, had the greatest impact on the solution quality.

Enterobacteriaceae represent a diverse and medically important family of bacteria that are difficult to identify to the species level using the standard molecular method of 16S rRNA gene sequencing. Prior work has demonstrated the value of dnaJ gene sequence analysis in resolving different members of the family. However, existing protocols are not optimized for clinical use and exhibit several limitations in practice. Here, we describe an improved assay for dnaJ-based identification of Enterobacteriaceae which boasts increased broad-range specificity across genera, shorter amplicon sizes that are suitable for use with formalin-fixed or direct patient specimens, and enhanced amplification efficiency and assay sensitivity through the incorporation of locked nucleic acid chemistries. Sequence analysis of public databases indicates that the partial dnaJ sequence interrogated by this design retains high discriminatory power among Enterobacteriaceae genera and species, with only particular lineages of Shigella sp. and Escherichia coli proving unresolvable. Limits of detection studies using 8 disparate species indicated that amplification was consistently achievable across organisms and allowed robust dideoxynucleotide chain terminator sequencing from as little as 10 genome equivalents of template, depending on the species interrogated. Retrospective application of the dnaJ assay to patient specimens enabled unambiguous classification of Enterobacteriaceae to the species level in 22 of 27 (81.5%) positive specimens examined, with most remaining cases representing unresolvable calls between closely related Escherichia coli and Shigella species. We expect that this assay will facilitate the accurate molecular identification of species from the Enterobacteriaceae family in a variety of clinical specimens and diagnostic contexts.

Low-treedepth colorings are an important tool for algorithms that exploit structure in classes of bounded expansion; they guarantee subgraphs that use few colors have bounded treedepth. These colorings have an implicit tradeoff between the total number of colors used and the treedepth bound, and prior empirical work suggests that the former dominates the run time of existing algorithms in practice. We introduce p-linear colorings as an alternative to the commonly used p-centered colorings. They can be efficiently computed in bounded expansion classes and use at most as many colors as p-centered colorings. Although a set of k<p colors from a p-centered coloring induces a subgraph of treedepth at most k, the same number of colors from a p-linear coloring may induce subgraphs of larger treedepth. We establish a polynomial upper bound on the treedepth in general graphs, and give tighter bounds in trees and interval graphs via constructive coloring algorithms. We also give a co-NP-completeness reduction for recognizing p-linear colorings and discuss ways to overcome this limitation in practice.

Lower and upper bounds on the maximum priority inversion blocking (pi-blocking) that is generally unavoidable in distributed multiprocessor real-time locking protocols (where resources may be accessed only from specific synchronization processors) are established. Prior work on suspension-based shared-memory multiprocessor locking protocols (which require resources to be accessible from all processors) has established asymptotically tight bounds of Ω(m) and Ω(n) maximum pi-blocking under suspension-oblivious and suspension-aware analysis, respectively, where m denotes the total number of processors and n denotes the number of tasks. In this paper, it is shown that, in the case of distributed semaphore protocols, there exist two different task allocation scenarios that give rise to distinct lower bounds. In the case of co-hosted task allocation, where application tasks may also be assigned to synchronization processors (i.e., processors hosting critical sections), Ω(Φ · n) maximum pi-blocking is unavoidable for some tasks under any locking protocol under both suspension-aware and suspension-oblivious schedulability analysis, where Φ denotes the ratio of the maximum response time to the shortest period. In contrast, in the case of disjoint task allocation (i.e., if application tasks may not be assigned to synchronization processors), only Ω(m) and Ω(n) maximum pi-blocking is fundamentally unavoidable under suspension-oblivious and suspension-aware analysis, respectively, as in the shared-memory case. These bounds are shown to be asymptotically tight with the construction of two new distributed real-time locking protocols that ensure O(m) and O(n) maximum pi-blocking under suspension-oblivious and suspension-aware analysis, respectively.

In our prior work, we presented a highly effective local search based heuristic algorithm called the largest expanding sweep search (LESS) to solve the minimum energy broadcast (MEB) problem over wireless ad hoc or sensor networks. In this paper, the performance is further strengthened by using iterated local optimization (ILO) techniques at the cost of additional computational complexity. To the best of our knowledge, this implementation constitutes currently the best performing algorithm among the known heuristics for MEB. We support this claim through extensive simulation study, comparing with globally optimal solutions obtained by an integer programming (IP) solver. For small network size up to 20 nodes, which is imposed by practical limitation of the IP solver, the ILO based algorithm produces globally optimal solutions with very high frequency (70%), and average performance is within 1.12% of the optimal solution.

Traffic measurement is key to many network management tasks such as performance monitoring and cyber-security. Its aim is to inspect the packet stream passing through a network device, classify them into flows according to the header fields, and obtain statistics about the flows. For processing big streaming data in size-limited SRAM of line cards, many space-sublinear algorithms have been proposed, such as CountMin and CountSketch. However, most of them are designed for specific measurement tasks. Implementing multiple independent sketches places burden for online operations of a network device. It is highly desired to design a universal sketch that not only tracks individual large flows (called heavy hitters) but also reports overall traffic distribution statistics (called moments). The prior work UnivMon successfully tackled this ambitious quest. However, it incurs large and variable per-packet processing overhead, which may result in a significant throughput bottleneck in high-rate packet streaming, given that each packet requires 65 hashes and 64 memory accesses on average and many times of that in the worst case. To address this performance issue, we need to fundamentally redesign the solution architecture from hierarchical sampling to new progressive sampling and from CountSketch to new ActiveCM+, which ensure that per-packet overhead is a small constant (4 hash and 4 memory accesses) in the worst case, making it much more suitable for online operations, especially for pipeline implementation. The new design also makes effort to reduce memory footprint or equivalently improve measurement accuracy under the same memory. Our experiments show that our solution incurs just one sixteenth per-packet overhead of UnivMon, while improving measurement accuracy by three times under the same memory.

This research was undertaken to quantify the structure of protein variation in a commercial hard red winter (HRW) wheat (Triticum aestivum L.) production system. This information will augment our knowledge and practices of sampling, segregating, marketing, and varietal development to improve uniformity and end‐use quality of HRW wheat. The allocation of kernel protein variance to specific components in southwestern Kansas was performed by a hierarchical sampling design. Sources of variability included Field, Plot (plots within a field), Row (rows within a plot), Plant (plants within a row), Head (heads within a plant), Position (spikelets at a specific position on a head), Spikelet (spikelets within a position), and Kernel (kernels within a spikelet). Individual kernels (10 152) were collected from 46 fields planted to one of four cultivars: Jagger, 2137, Ike, or TAM 107. Kernels were evaluated for protein concentration by a single kernel characterization system equipped with a diode array near‐infrared (NIR) spectrometer. For the cultivars 2137 and Ike, all sources of variability except Spikelet were statistically significant (P &lt; 0.05). For Jagger, all sources except Row were significant and for TAM 107, variation attributed to Field and Plant were not significant. Field and Plot sources of variability contributed the greatest amount of variance within the hierarchy for Jagger, 2137, and Ike. For TAM 107, Plot was the greatest source of variability. The least squares means were calculated for the fixed effect Position. Jagger, Ike, and 2137 showed a significant protein gradient in which the highest protein concentration occurred at the base of the head and the lowest protein content at the top. For TAM 107, the greatest protein content was found at the base. Results of this study provide a benchmark for future efforts to improve wheat consistency through breeding and crop management. The protein variance structure described during this study also defines practical limits for managing and marketing protein content in HRW.

Systematic investigations were carried out into the sorption of REEs, Y and Sc on activated carbon. Experimental parameters, such as the effect of pH, amount of carbon, contact time, sample solution volume and various mineral acids for desorption, were optimized for quantitative recoveries. The procedure was applied to the determination of REEs in Indian sea-water and groundwater by ICP-MS. The practical limit of determination with an enrichment factor of 400 is 0.3 pg ml–1(based on the preconcentration of 2000 ml of sample to 5 ml). The precision of the method is 10% at the 0.3 pg ml–1 level. The preconcentration method is simple, expeditious and field-oriented with a simple single-stage separation of the REEs from Ba and the salt content.