An efficient design space exploration framework to optimize power-efficient heterogeneous many-core multi-threading embedded processor architectures

By the middle of this decade, uniprocessor architecture performance had hit a roadblock due to a combination of factors, such as excessive power dissipation due to high operating frequencies, growing memory access latencies, diminishing returns on deeper instruction pipelines, and a saturation of available instruction level parallelism in applications. An attractive and viable alternative embraced by all the processor vendors was multi-core architectures where throughput is improved by using micro-architectural features such as multiple processor cores, interconnects and low latency shared caches integrated on a single chip. The individual cores are often simpler than uniprocessor counterparts, use hardware multi-threading to exploit thread-level parallelism and latency hiding and typically achieve better performance-power figures. The overwhelming success of the multi-core microprocessors in both high performance and embedded computing platforms motivated chip architects to dramatically scale the multi-core processors to many-cores which will include hundreds of cores on-chip to further improve throughput. With such complex large scale architectures however, several key design issues need to be addressed. First, a wide range of micro- architectural parameters such as L1 caches, load/store queues, shared cache structures and interconnection topologies and non-linear interactions between them define a vast non-linear multi-variate micro-architectural design space of many-core processors; the traditional method of using extensive in-loop simulation to explore the design space is simply not practical. Second, to accurately evaluate the performance (measured in terms of cycles per instruction (CPI)) of a candidate design, the contention at the shared cache must be accounted in addition to cycle-by-cycle behavior of the large number of cores which superlinearly increases the number of simulation cycles per iteration of the design exploration. Third, single thread performance does not scale linearly with number of hardware threads per core and number of cores due to memory wall effect. This means that at every step of the design process designers must ensure that single thread performance is not unacceptably slowed down while increasing overall throughput. While all these factors affect design decisions in both high performance and embedded many-core processors, the design of embedded processors required for complex embedded applications such as networking, smart power grids, battlefield decision-making, consumer electronics and biomedical devices to name a few, is fundamentally different from its high performance counterpart because of the need to consider (i) low power and (ii) real-time operations. This implies the design objective for embedded many-core processors cannot be to simply maximize performance, but improve it in such a way that overall power dissipation is minimized and all real-time constraints are met. This necessitates additional power estimation models right at the design stage to accurately measure the cost and reliability of all the candidate designs during the exploration phase. In this dissertation, a statistical machine learning (SML) based design exploration framework is presented which employs an execution-driven cycle- accurate simulator to accurately measure power and performance of embedded many-core processors. The embedded many-core processor domain is Network Processors (NePs) used to processed network IP packets. Future generation NePs required to operate at terabits per second network speeds captures all the aspects of a complex embedded application consisting of shared data structures, large volume of compute-intensive and data-intensive real-time bound tasks and a high level of task (packet) level parallelism. Statistical machine learning (SML) is used to efficiently model performance and power of candidate designs in terms of wide ranges of micro-architectural parameters. The method inherently minimizes number of in-loop simulations in the exploration framework and also efficiently captures the non-linear interactions between the micro-architectural design parameters. To ensure scalability, the design space is partitioned into (i) core-level micro-architectural parameters to optimize single core architectures subject to the real-time constraints and (ii) shared memory level micro- architectural parameters to explore the shared interconnection network and shared cache memory architectures and achieves overall optimality. The cost function of our exploration algorithm is the total power dissipation which is minimized, subject to the constraints of real-time throughput (as determined from the terabit optical network router line-speed) required in IP packet processing embedded application

Impact of tomato juice on radiation side effects and select inflammatory mediators in prostate cancer patients undergoing intensity modulated radiation therapy

This pilot study assessed tolerance of different volumes of processed tomato juice consumed daily and its impact on serum lycopene, selected serum inflammatory mediator levels and radiation-induced side effects in men with localized prostate cancer undergoing radiation therapy. Participants (n = 17) were randomized into control group or one of three intervention groups (4 oz, 8 oz or 12 oz of processed tomato juice daily). Non-Hispanic Whites comprised 71% of study participants. Tumor staging ranged from T1c-2cN0M0, with 71% of participant tumors in the T1cN0M0 stage. Participants tolerated daily tomato juice supplementation without any adverse gastrointestinal (GI) effects. Serum lycopene decreased in control group participants, while increasing from 0.33±0.11 ìg/mL (baseline) to 0.41± 0.12 ìg/mL (endpoint) in the intervention group. No correlation between serum and dietary lycopene was detected. Control group participants lost weight, while participants in the intervention groups did not. Not surprisingly, participants exhibited systemic inflammation at baseline. Overtime, increased c-reactive protein (CRP) and interleukin-6 (IL-6) was observed in control group, while decreases in serum CRP, IL-6 and prostaglandin E2 (PGE2) levels were observed in intervention groups (p>0.05). No statistically significant within group differences were detected for CRP. Within group differences were statistically significant for 12 oz group only, when comparing baseline and endpoint with midpoint levels (p = 0.014) for IL-6, and when comparing PGE2 baseline levels with midpoint and endpoint (p = 0.003). We observed no statistical correlation between inflammatory markers, cancer characteristics and dietary or serum lycopene, or acute side effects of treatment. Lower performance score was observed in intervention group participants. Daily tomato juice intake appeared to offer a GI protective effect during the first three weeks of treatment. Based on the results of this study, daily consumption of processed tomato juice (at least 8-12 oz) may decrease serum levels of CRP, IL-6 and PGE2; lower performance status score; and offer a protective GI effect during radiotherapy for prostate cancer. This information may assist in improving patient tolerance and minimize acute side-effects of radiation therapy in men with localized prostate cancer undergoing intensity modulated radiation therapy

Influence of Matrix Polarity on the Properties of Ethylene Vinyl Acetate–Carbon Nanofiller Nanocomposites

A series of ethylene vinyl acetate (EVA) nanocomposites using four kinds of EVA with 40, 50, 60, and 70 wt% vinyl acetate (VA) contents and three different carbon-based nanofillers—expanded graphite (EG), multi-walled carbon nanotube (MWCNT), and carbon nanofiber (CNF) have been prepared via solution blending. The influence of the matrix polarity and the nature of nanofillers on the morphology and properties of EVA nanocomposites have been investigated. It is observed that the sample with lowest vinyl acetate content exhibits highest mechanical properties. However, the enhancement in mechanical properties with the incorporation of various nanofillers is the highest for EVA with high VA content. This trend has been followed in both dynamic mechanical properties and thermal conductivity of the nanocomposites. EVA copolymer undergoes a transition from partial to complete amorphousness between 40 and 50 wt% VA content, and this changes the dispersion of the nanofillers. The high VA-containing polymers show more affinity toward fillers due to the large free volume available and allow easy dispersion of nanofillers in the amorphous rubbery phase, as confirmed from the morphological studies. The thermal stability of the nanocomposites is also influenced by the type of nanofiller

Mass spectrometry and multivariate analysis to classify cervical intraepithelial neoplasia from blood plasma: an untargeted lipidomic study

Cervical cancer is still an important issue of public health since it is the fourth most frequent type of cancer in women worldwide. Much effort has been dedicated to combating this cancer, in particular by the early detection of cervical pre-cancerous lesions. For this purpose, this paper reports the use of mass spectrometry coupled with multivariate analysis as an untargeted lipidomic approach to classifying 76 blood plasma samples into negative for intraepithelial lesion or malignancy (NILM, n = 42) and squamous intraepithelial lesion (SIL, n = 34). The crude lipid extract was directly analyzed with mass spectrometry for untargeted lipidomics, followed by multivariate analysis based on the principal component analysis (PCA) and genetic algorithm (GA) with support vector machines (SVM), linear (LDA) and quadratic (QDA) discriminant analysis. PCA-SVM models outperformed LDA and QDA results, achieving sensitivity and specificity values of 80.0% and 83.3%, respectively. Five types of lipids contributing to the distinction between NILM and SIL classes were identified, including prostaglandins, phospholipids, and sphingolipids for the former condition and Tetranor-PGFM and hydroperoxide lipid for the latter. These findings highlight the potentiality of using mass spectrometry associated with chemometrics to discriminate between healthy women and those suffering from cervical pre-cancerous lesions

Development of a peer support intervention to encourage dietary behaviour change towards a Mediterranean diet in adults at high cardiovascular risk.

BACKGROUND: Mediterranean diet (MD) interventions are demonstrated to significantly reduce cardiovascular disease (CVD) risk but are typically resource intensive and delivered by health professionals. There is considerable interest to develop interventions that target sustained dietary behaviour change and that are feasible to scale-up for wider public health benefit. The aim of this paper is to describe the process used to develop a peer support intervention to encourage dietary behaviour change towards a MD in non-Mediterranean adults at high CVD risk. METHODS: The Medical Research Council (MRC) and Behaviour Change Wheel (BCW) frameworks and the COM-B (Capability, Opportunity, Motivation, Behaviour) theoretical model were used to guide the intervention development process. We used a combination of evidence synthesis and qualitative research with the target population, health professionals, and community health personnel to develop the intervention over three main stages: (1) we identified the evidence base and selected dietary behaviours that needed to change, (2) we developed a theoretical basis for how the intervention might encourage behaviour change towards a MD and selected intervention functions that could drive the desired MD behaviour change, and (3) we defined the intervention content and modelled outcomes. RESULTS: A theory-based, culturally tailored, peer support intervention was developed to specifically target behaviour change towards a MD in the target population. The intervention was a group-based program delivered by trained peer volunteers over 12-months, and incorporated strategies to enhance social support, self-efficacy, problem-solving, knowledge, and attitudes to address identified barriers to adopting a MD from the COM-B analysis. CONCLUSIONS: The MRC and BCW frameworks provided a systematic and complementary process for development of a theory-based peer support intervention to encourage dietary behaviour change towards a MD in non-Mediterranean adults at high CVD risk. The next step is to evaluate feasibility, acceptability, and diet behaviour change outcomes in response to the peer support intervention (change towards a MD and nutrient biomarkers) using a randomized controlled trial design

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Abstract Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images

Differential gene expression in nearly isogenic lines with QTL for partial resistance to Puccinia hordei in barley

<p>Abstract</p> <p>Background</p> <p>The barley-<it>Puccinia hordei </it>(barley leaf rust) pathosystem is a model for investigating partial disease resistance in crop plants and genetic mapping of phenotypic resistance has identified several quantitative trait loci (QTL) for partial resistance. Reciprocal QTL-specific near-isogenic lines (QTL-NILs) have been developed that combine two QTL, <it>Rphq</it>2 and <it>Rphq</it>3, the largest effects detected in a recombinant-inbred-line (RIL) population derived from a cross between the super-susceptible line L94 and partially-resistant line Vada. The molecular mechanism underpinning partial resistance in these QTL-NILs is unknown.</p> <p>Results</p> <p>An Agilent custom microarray consisting of 15,000 probes derived from barley consensus EST sequences was used to investigate genome-wide and QTL-specific differential expression of genes 18 hours post-inoculation (hpi) with <it>Puccinia hordei</it>. A total of 1,410 genes were identified as being significantly differentially expressed across the genome, of which 55 were accounted for by the genetic differences defined by QTL-NILs at <it>Rphq</it>2 and <it>Rphq</it>3. These genes were predominantly located at the QTL regions and are, therefore, positional candidates. One gene, encoding the transcriptional repressor Ethylene-Responsive Element Binding Factor 4 (<it>HvERF4</it>) was located outside the QTL at 71 cM on chromosome 1H, within a previously detected eQTL hotspot for defence response. The results indicate that <it>Rphq</it>2 or <it>Rphq</it>3 contains a <it>trans</it>-eQTL that modulates expression of <it>HvERF4</it>. We speculate that HvERF4 functions as an intermediate that conveys the response signal from a gene(s) contained within <it>Rphq</it>2 or <it>Rphq</it>3 to a host of down-stream defense responsive genes. Our results also reveal that barley lines with extreme or intermediate partial resistance phenotypes exhibit a profound similarity in their spectrum of <it>Ph</it>-responsive genes and that hormone-related signalling pathways are actively involved in response to <it>Puccinia hordei</it>.</p> <p>Conclusions</p> <p>Differential gene expression between QTL-NILs identifies genes predominantly located within the target region(s) providing both transcriptional and positional candidate genes for the QTL. Genetically mapping the differentially expressed genes relative to the QTL has the potential to discover <it>trans</it>-eQTL mediated regulatory relays initiated from genes within the QTL regions.</p

Poly(I:C) Enhances the Susceptibility of Leukemic Cells to NK Cell Cytotoxicity and Phagocytosis by DC

α Active specific immunotherapy aims at stimulating the host's immune system to recognize and eradicate malignant cells. The concomitant activation of dendritic cells (DC) and natural killer (NK) cells is an attractive modality for immune-based therapies. Inducing immunogenic cell death to facilitate tumor cell recognition and phagocytosis by neighbouring immune cells is of utmost importance for guiding the outcome of the immune response. We previously reported that acute myeloid leukemic (AML) cells in response to electroporation with the synthetic dsRNA analogue poly(I:C) exert improved immunogenicity, demonstrated by enhanced DC-activating and NK cell interferon-γ-inducing capacities. To further invigorate the potential of these immunogenic tumor cells, we explored their effect on the phagocytic and cytotoxic capacity of DC and NK cells, respectively. Using single-cell analysis, we assessed these functionalities in two- and three-party cocultures. Following poly(I:C) electroporation AML cells become highly susceptible to NK cell-mediated killing and phagocytosis by DC. Moreover, the enhanced killing and the improved uptake are strongly correlated. Interestingly, tumor cell killing, but not phagocytosis, is further enhanced in three-party cocultures provided that these tumor cells were upfront electroporated with poly(I:C). Altogether, poly(I:C)-electroporated AML cells potently activate DC and NK cell functions and stimulate NK-DC cross-talk in terms of tumor cell killing. These data strongly support the use of poly(I:C) as a cancer vaccine component, providing a way to overcome immune evasion by leukemic cells