HTA: A Scalable High-Throughput Accelerator for Irregular HPC Workloads

We propose a new architecture called HTA for high throughput irregular HPC applications with little data reuse. HTA reduces the contention within the memory system with the help of a partitioned memory controller that is amenable for 2.5D implementation using Silicon Photonics. In terms of scalability, HTA supports 4 × higher number of compute units compared to the state-of-the-art GPU systems. Our simulation-based evaluation on a representative set of HPC benchmarks shows that the proposed design reduces the queuing latency by 10% to 30%, and improves the variability in memory access latency by 10% to 60%. Our results show that the HTA improves the L1 miss penalty by 2.3 × to 5 × over GPUs. When compared to a multi-GPU system with the same number of compute units, our simulation results show that the HTA can provide up to 2 × speedup

Data-Driven Structural Health Monitoring in Laminated Composite Structures: Characterisation of Impact Damage

There is a high level of uncertainty for detecting damage, such as barely visible impact damage, hidden manufacturing defects, and subsurface cracks in laminated composites, which is a main limiting factor in wider use of these materials. This highlights the necessity of developing innovative structural health monitoring (SHM) strategies to meet the safety and reliability of current composite structures. In this research, a wide range of laminated composite specimens were designed, manufactured and tested under drop-weight impact with several impact energies to generate visual evidence of such impact events. The dataset was then used to train a user developed artificial intelligence (AI)-based algorithm to identify and predict damaged areas. The results showed that the developed algorithm could well identify the impact damage on both front and back faces of the specimens. The results obtained from the new AI-based platform were in good agreement with visual observations. The research highlights the importance of a high quality dataset in training the AI-based algorithms for visual SHM

Demo abstract: RadiaLE: a framework for benchmarking link quality estimators

Link quality estimation is a fundamental building block for the design of several different mechanisms and protocols in wireless sensor networks (WSN). A thorough experimental evaluation of link quality estimators (LQEs) is thus mandatory. Several WSN experimental testbeds have been designed ([1–4]) but only [3] and [2] targeted link quality measurements. However, these were exploited for analyzing low-power links characteristics rather than the performance of LQEs. Despite its importance, the experimental performance evaluation of LQEs remains an open problem, mainly due to the difficulty to provide a quantitative evaluation of their accuracy. This motivated us to build a benchmarking testbed for LQE - RadiaLE, which we present here as a demo. It includes (i.) hardware components that represent the WSN under test and (ii.) a software tool for the set up and control of the experiments and also for analyzing the collected data, allowing for LQEs evaluation

State of energy estimation in electric propulsion systems with lithium-sulfur batteries

Lithium-Sulfur (Li-S) batteries are an emerging and appealing electrical energy storage technology. The literature on the Stateof- charge (SoC) estimation of Li-S is readily available. In real-world, battery operated vehicles and equipment need to monitor the electrical energy. This paper focuses on State-of-Eneergy (SoE) estimation of Li-S battery based electric propulsion system. This paper bridges literature gap of the SoE estimation of Li-S battery. While comparing mathematically, the definition of the SoC and SoE batteries are different. Reviewing the SoC estimation, this paper compares the SoC and SoE estimation for same data set. The challenges in Li-S SoC and SoE estimation include battery modelling and time-varying parameters and nonlinear voltage measurement, which has deeply skewed high-plateau and flatted low-plateau characteristics. Modelling Li-S battery as a Thevenin’s equivalent circuit network (ECN), the battery parameters are estimated using Predict Error Minimization (PEM) approach. For estimate SoC and SoE, the extended Kalman filter (EKF) is used. Since the parameters are high sensitive to battery current, the estimators use parameters obtained by polynomial fitting model. A simple switching logic based on SoCmeasurement voltage is used to join the high- and low-plateau. The degree of observability analysis is used to investigate the performance of SoE estimation by the EKF. Using experiment test data, simulation results demonstrate the performance of both SoC and SoE estimators. Results show that the SoE estimation is as close to the SoC estimatio

Preoperative 99mTc-sestamibi scintigraphy in patients with primary hyperparathyroidism and concomitant nodular goiter: Comparison of SPECT-CT, SPECT, and planar imaging

Background: Investigations using a hybrid single photon emission computed tomography/computed tomography (SPECT-CT) scanning technique have been carried out in limited studies and have shown mixed results. However, the assessment of this technique for the detection of parathyroid adenoma in patients with a nodular goiter was performed in only one study with a small sample size. The aim of this prospective study was to assess the role of Tc-sestamibi parathyroid SPECT-CT scans for localization of parathyroid adenomas with a concomitant nodular goiter using Tc-methoxyisobutyl isonitrile (MIBI) scintigraphy and to compare it with SPECT and planar imaging. Methods: This study was conducted on 48 patients with primary hyperparathyroidism and nodular goiter, who were candidates for parathyroid surgery and had been referred for parathyroid scintigraphy. The patients underwent an early set of planar Tc-MIBI scanning procedures first, followed by SPECT and CT scannings, and finally a delayed set of planar Tc-MIBI scannings. Sensitivity, specificity, negative and positive predictive values, and accuracy were determined on a per-parathyroid-gland basis for each scanning method, as defined by histology and follow-up. Results: The surgery was successful in 48 out of 50 patients with primary hyperparathyroidism concomitant with thyroid nodularity, and data were completed for 80 sites in 48 patients. The accuracy of SPECT-CT in correctly identifying a parathyroid adenoma was 85.00, versus 75.00% for SPECT (P=0.01, significant). The sensitivity and specificity for SPECT-CT were 77.55 and 96.77%, respectively, versus 67.34 and 87.09%, respectively, for SPECT (P=0.12 and 0.12, not significant). There were nine sites that showed better localization on SPECT-CT scans relative to SPECT images, of which five sites were located in the ectopic regions. Conclusion: The results of our study indicate that SPECT-CT is more accurate than sestamibi planar imaging and SPECT for the preoperative identification of parathyroid lesions in patients with primary hyperparathyroidism concomitant with thyroid nodularity. Also, we would recommend the use of SPECT-CT for a workup of all patients with ectopic glands who are scheduled for minimally invasive parathyroid surgery. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins

Eye care utilization patterns in Tehran population: a population based cross-sectional study

BACKGROUND: The aim of this study is to determine eye care visits which are an indicator of eye care service utilization by Tehran population and its determinants. METHODS: Through a population-based, cross-sectional study, 6497 Tehran citizens were sampled. All participants had complete eye examinations and an interview regarding demographic and socioeconomic status variables, past medical and eye history, and their previous and last eye care visits. RESULTS: Among those sampled, 4565 people participated in the study (response rate of 70.3%). Among these participants, 34.7 % had never visited an ophthalmologist or optometrist (95% confidence interval [CI]: 32.4 to 36.9) and 43.2% had not seen an eye care provider in the last 5 years. Multivariate logistic regression revealed that men (OR = 1.30), younger participants (each year increase in age: OR = 0.98) and the less educated (each year increase in education: OR = 0.93) were more likely, and the visually impaired were less likely (OR = 0.41) to have neglected eye care. CONCLUSION: A large proportion of the population, including those in the high risk group who require eye care, has never utilized any eye care service. These data suggest that efforts have to be made to better understand the causes and to optimize the utilization of the available eye care services in the population

LLM: Realizing Low-Latency Memory by Exploiting Embedded Silicon Photonics for Irregular Workloads

As emerging workloads exhibit irregular memory access patterns with poor data reuse and locality, they would benefit from a DRAM that achieves low latency without sacrificing bandwidth and energy efficiency. We propose LLM (Low Latency Memory), a codesign of the DRAM microarchitecture, the memory controller and the LLC/DRAM interconnect by leveraging embedded silicon photonics in 2.5D/3D integrated system on chip. LLM relies on Wavelength Division Multiplexing (WDM)-based photonic interconnects to reduce the contention throughout the memory subsystem. LLM also increases the bank-level parallelism, eliminates bus conflicts by using dedicated optical data paths, and reduces the access energy per bit with shorter global bitlines and smaller row buffers. We evaluate the design space of LLM for a variety of synthetic benchmarks and representative graph workloads on a full-system simulator (gem5). LLM exhibits low memory access latency for traffics with both regular and irregular access patterns. For irregular traffic, LLM achieves high bandwidth utilization (over 80% peak throughput compared to 20% of HBM2.0). For real workloads, LLM achieves 3 × and 1.8 × lower execution time compared to HBM2.0 and a state-of-the-art memory system with high memory level parallelism, respectively. This study also demonstrates that by reducing queuing on the data path, LLM can achieve on average 3.4 × lower memory latency variation compared to HBM2.0