An empirical evaluation of High-Level Synthesis languages and tools for database acceleration

High Level Synthesis (HLS) languages and tools are emerging as the most promising technique to make FPGAs more accessible to software developers. Nevertheless, picking the most suitable HLS for a certain class of algorithms depends on requirements such as area and throughput, as well as on programmer experience. In this paper, we explore the different trade-offs present when using a representative set of HLS tools in the context of Database Management Systems (DBMS) acceleration. More specifically, we conduct an empirical analysis of four representative frameworks (Bluespec SystemVerilog, Altera OpenCL, LegUp and Chisel) that we utilize to accelerate commonly-used database algorithms such as sorting, the median operator, and hash joins. Through our implementation experience and empirical results for database acceleration, we conclude that the selection of the most suitable HLS depends on a set of orthogonal characteristics, which we highlight for each HLS framework.Peer ReviewedPostprint (author’s final draft

Res Medica, Autumn 1959, Volume 2, Number 1

TABLE OF CONTENTSSYLLABUS FOR THE 223RD SESSIONHYPOTENSIVE DRUGS: G. E. Mawer, B.ScAN OCULIST LOOKS ATENDOCRINE EXOPHTHALMOS: C. R. S. Jackson.M.A., M.D., D.O.M .S., F.R.C.S.E.RES MEDICA THE TREATMENT OF CANCER: John McKendrick,M.B., Ch.B.DOCTORS AND ARTISTS: Professor W. I. C.Morris, F.R.C.S.E.SOME ASPECTS OFRHEUMATIC FEVER: David J. ClarkABDOMINAL PAIN: Geoffrey T. Millar,M.B., Ch.B.TWO HUNDRED YEARS AGO: James A. Gray, M.B..Ch.B

Integrating Algorithmic Parameters into Benchmarking and Design Space Exploration in 3D Scene Understanding

System designers typically use well-studied benchmarks to evaluate and improve new architectures and compilers. We design tomorrow's systems based on yesterday's applications. In this paper we investigate an emerging application, 3D scene understanding, likely to be signi cant in the mobile space in the near future. Until now, this application could only run in real-time on desktop GPUs. In this work, we examine how it can be mapped to power constrained embedded systems. Key to our approach is the idea of incremental co-design exploration, where optimization choices that concern the domain layer are incrementally explored together with low-level compiler and architecture choices. The goal of this exploration is to reduce execution time while minimizing power and meeting our quality of result objective. As the design space is too large to exhaustively evaluate, we use active learning based on a random forest predictor to nd good designs. We show that our approach can, for the rst time, achieve dense 3D mapping and tracking in the real-time range within a 1W power budget on a popular embedded device. This is a 4.8x execution time improvement and a 2.8x power reduction compared to the state-of-the-art

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their high computational requirements mean that use on mass market embedded platforms is challenging. Meanwhile, trends in low-cost, low-power processing are towards massive parallelism and heterogeneity, making it difficult for robotics and vision researchers to implement their algorithms in a performance-portable way. In this paper we introduce SLAMBench, a publicly-available software framework which represents a starting point for quantitative, comparable and validatable experimental research to investigate trade-offs in performance, accuracy and energy consumption of a dense RGB-D SLAM system. SLAMBench provides a KinectFusion implementation in C++, OpenMP, OpenCL and CUDA, and harnesses the ICL-NUIM dataset of synthetic RGB-D sequences with trajectory and scene ground truth for reliable accuracy comparison of different implementation and algorithms. We present an analysis and breakdown of the constituent algorithmic elements of KinectFusion, and experimentally investigate their execution time on a variety of multicore and GPUaccelerated platforms. For a popular embedded platform, we also present an analysis of energy efficiency for different configuration alternatives.Comment: 8 pages, ICRA 2015 conference pape

Bone turnover in elderly men: relationships to change in bone mineral density

BACKGROUND: It is not clear whether bone turnover markers can be used to make inference regarding changes in bone mineral density (BMD) in untreated healthy elderly men. The present study was designed to address three specific questions: (i) is there a relationship between bone turnover markers and femoral neck BMD within an individual; (ii) is there a relationship between baseline measurements of bone turnover markers and subsequent change in BMD; and (iii) is there a relationship between changes in bone turnover markers and changes in femoral neck BMD? METHODS: The present study was part of the on-going Dubbo Osteoporosis Epidemiology Study, which was designed as a prospective investigation. Men who had had at least 3 sequential visits with serum samples available during follow-up were selected from the study population. Serum C-terminal telopeptide of type I collagen (sICTP), N-terminal propeptide of type I collagen (sPINP) and femoral neck BMD were measured by competitive radioimmunoassays. Femoral neck bone mineral density (BMD) was measured by a densitometer (GE Lunar Corp, Madison, WI). Various mixed-effects models were used to assess the association between the markers and changes in BMD. RESULTS: One hundred and one men aged 70 ± 4.1 years (mean ± SD) met the criteria of selection for analysis. On average, sPINP decreased by 0.7% per year (p = 0.026), sICTP increased by 1.7% per year (p = 0.0002), and femoral neck BMD decreased by 0.4% per year (p < 0.01). Within-subject analysis indicated that changes in BMD were significantly associated with changes in sPINP (p = 0.022), but not with changes in sICTP (p = 0.84). However, neither baseline sPINP (p = 0.50) nor baseline sICTP (p = 0.63) was associated with subsequent changes in BMD. Moreover, changes in BMD were not significantly associated with previous changes in sPINP (p = 0.13) or sICTP (p = 0.95). CONCLUSION: These results suggest that in elderly men of Caucasian background, changes in sPINP were inversely related to changes in BMD within an individual. However, neither sPINP nor sICTP was sufficiently sensitive to predict the rate of change in BMD for a group of individuals or for an individual

Navigating the Landscape for Real-time Localisation and Mapping for Robotics, Virtual and Augmented Reality

Visual understanding of 3D environments in real-time, at low power, is a huge computational challenge. Often referred to as SLAM (Simultaneous Localisation and Mapping), it is central to applications spanning domestic and industrial robotics, autonomous vehicles, virtual and augmented reality. This paper describes the results of a major research effort to assemble the algorithms, architectures, tools, and systems software needed to enable delivery of SLAM, by supporting applications specialists in selecting and configuring the appropriate algorithm and the appropriate hardware, and compilation pathway, to meet their performance, accuracy, and energy consumption goals. The major contributions we present are (1) tools and methodology for systematic quantitative evaluation of SLAM algorithms, (2) automated, machine-learning-guided exploration of the algorithmic and implementation design space with respect to multiple objectives, (3) end-to-end simulation tools to enable optimisation of heterogeneous, accelerated architectures for the specific algorithmic requirements of the various SLAM algorithmic approaches, and (4) tools for delivering, where appropriate, accelerated, adaptive SLAM solutions in a managed, JIT-compiled, adaptive runtime context.Comment: Proceedings of the IEEE 201

Tumor-Infiltrating T Cells Correlate with NY-ESO-1-Specific Autoantibodies in Ovarian Cancer

BACKGROUND: Tumor-infiltrating CD8+ T cells are correlated with prolonged progression-free and overall survival in epithelial ovarian cancer (EOC). A significant fraction of EOC patients mount autoantibody responses to various tumor antigens, however the relationship between autoantibodies and tumor-infiltrating T cells has not been investigated in EOC or any other human cancer. We hypothesized that autoantibody and T cell responses may be correlated in EOC and directed toward the same antigens. METHODOLOGY AND PRINCIPAL FINDINGS: We obtained matched serum and tumor tissue from 35 patients with high-grade serous ovarian cancer. Serum samples were assessed by ELISA for autoantibodies to the common tumor antigen NY-ESO-1. Tumor tissue was examined by immunohistochemistry for expression of NY-ESO-1, various T cell markers (CD3, CD4, CD8, CD25, FoxP3, TIA-1 and Granzyme B) and other immunological markers (CD20, MHC class I and MHC class II). Lymphocytic infiltrates varied widely among tumors and included cells positive for CD3, CD8, TIA-1, CD25, FoxP3 and CD4. Twenty-six percent (9/35) of patients demonstrated serum IgG autoantibodies to NY-ESO-1, which were positively correlated with expression of NY-ESO-1 antigen by tumor cells (r = 0.57, p = 0.0004). Autoantibodies to NY-ESO-1 were associated with increased tumor-infiltrating CD8+, CD4+ and FoxP3+ cells. In an individual HLA-A2+ patient with autoantibodies to NY-ESO-1, CD8+ T cells isolated from solid tumor and ascites were reactive to NY-ESO-1 by IFN-gamma ELISPOT and MHC class I pentamer staining. CONCLUSION AND SIGNIFICANCE: We demonstrate that tumor-specific autoantibodies and tumor-infiltrating T cells are correlated in human cancer and can be directed against the same target antigen. This implies that autoantibodies may collaborate with tumor-infiltrating T cells to influence clinical outcomes in EOC. Furthermore, serological screening methods may prove useful for identifying clinically relevant T cell antigens for immunotherapy

Nutrition and cancer: A review of the evidence for an anti-cancer diet

It has been estimated that 30–40 percent of all cancers can be prevented by lifestyle and dietary measures alone. Obesity, nutrient sparse foods such as concentrated sugars and refined flour products that contribute to impaired glucose metabolism (which leads to diabetes), low fiber intake, consumption of red meat, and imbalance of omega 3 and omega 6 fats all contribute to excess cancer risk. Intake of flax seed, especially its lignan fraction, and abundant portions of fruits and vegetables will lower cancer risk. Allium and cruciferous vegetables are especially beneficial, with broccoli sprouts being the densest source of sulforophane. Protective elements in a cancer prevention diet include selenium, folic acid, vitamin B-12, vitamin D, chlorophyll, and antioxidants such as the carotenoids (α-carotene, β-carotene, lycopene, lutein, cryptoxanthin). Ascorbic acid has limited benefits orally, but could be very beneficial intravenously. Supplementary use of oral digestive enzymes and probiotics also has merit as anticancer dietary measures. When a diet is compiled according to the guidelines here it is likely that there would be at least a 60–70 percent decrease in breast, colorectal, and prostate cancers, and even a 40–50 percent decrease in lung cancer, along with similar reductions in cancers at other sites. Such a diet would be conducive to preventing cancer and would favor recovery from cancer as well