Unleashing Fine-Grained Parallelism on Embedded Many-Core Accelerators with Lightweight OpenMP Tasking

In recent years, programmable many-core accelerators (PMCAs) have been introduced in embedded systems to satisfy stringent performance/Watt requirements. This has increased the urge for programming models capable of effectively leveraging hundreds to thousands of processors. Task-based parallelism has the potential to provide such capabilities, offering high-level abstractions to outline abundant and irregular parallelism in embedded applications. However, efficiently supporting this programming paradigm on embedded PMCAs is challenging, due to the large time and space overheads it introduces. In this paper we describe a lightweight OpenMP tasking runtime environment (RTE) design for a state-of-the-art embedded PMCA, the Kalray MPPA 256. We provide an exhaustive characterization of the costs of our RTE, considering both synthetic workload and real programs, and we compare to several other tasking RTEs. Experimental results confirm that our solution achieves near-ideal parallelization speedups for tasks as small as 5K cycles, and an average speedup of 12 × for real benchmarks, which is 60% higher than what we observe with the original Kalray OpenMP implementation

Self-Aware Thermal Management for High-Performance Computing Processors

Editor's note: Thermal management in high-performance multicore platforms has become exceedingly complex due to variable workloads, thermal heterogeneity, and long, thermal transients. This article addresses these complexities by sophisticated analysis of noisy thermal sensor readings, dynamic learning to adapt to the peculiarities of the hardware and the applications, and a dynamic optimization strategy. - Axel Jantsch, TU Wien - Nikil Dutt, University of California at Irvine

Power and Thermal Management Runtimes for HPC Applications in the Era of Exascale Computing

In the scope of technical and scientific computing the rush towards larger simulations, has been so far assisted by a steady downsizing of micro-processing units, which has allowed to increase the compute capacity of general-purpose architectures at constant power. As side effects of the end of Dennard's scaling, this process is now hitting its ultimate power limits and is just about to come to an end. The continuous grow of power consumption in supercomputers, requires a well-defined power budget at design time which should considers the worst-case power consumption to avoid outages. But supercomputers rarely cause the worst-case power consumption during their lifetime limiting the performance achievable in normal conditions. Another drawback of the end of the Dennard's scaling is that power density starts to increase at every technological step leading to overheating and thermal gradients. As result, thermal-bound machines show performance degradation and heterogeneity which limit the peak performance of the system. Moreover, it is well known that in large application runs, the time spent by the application in the communication is not negligible and impacts the power consumption of the system. This thesis presents software strategies to tackle the main bottlenecks induced by power and thermal issues that affects next-generation supercomputers. The thesis targets scientific applications which are the principal candidates “suffering” from the power and thermal constraints of supercomputers. To respond to the above challenges, this work shows that propagating workload requirements from application to the runtime and operating system levels is the key to provide efficiency. This is possible only if the proposed software methodologies cause little or no overhead in term of application performance. The experimental results show a significant step forward with respect to the current state-of-the-art solutions in power and thermal control of HPC systems

The Emotion Probe: On the Universality of Cross-Linguistic and Cross-Gender Speech Emotion Recognition via Machine Learning

Machine Learning (ML) algorithms within a human–computer framework are the leading force in speech emotion recognition (SER). However, few studies explore cross-corpora aspects of SER; this work aims to explore the feasibility and characteristics of a cross-linguistic, cross-gender SER. Three ML classifiers (SVM, Naïve Bayes and MLP) are applied to acoustic features, obtained through a procedure based on Kononenko’s discretization and correlation-based feature selection. The system encompasses five emotions (disgust, fear, happiness, anger and sadness), using the Emofilm database, comprised of short clips of English movies and the respective Italian and Spanish dubbed versions, for a total of 1115 annotated utterances. The results see MLP as the most effective classifier, with accuracies higher than 90% for single-language approaches, while the cross-language classifier still yields accuracies higher than 80%. The results show cross-gender tasks to be more difficult than those involving two languages, suggesting greater differences between emotions expressed by male versus female subjects than between different languages. Four feature domains, namely, RASTA, F0, MFCC and spectral energy, are algorithmically assessed as the most effective, refining existing literature and approaches based on standard sets. To our knowledge, this is one of the first studies encompassing cross-gender and cross-linguistic assessments on SER

Over-the-scope clip and self-expandable metal stent: a comprehensive treatment for failed peroral endoscopic myotomy and fibrosis complications in idiopathic achalasia

Achalasia is a rare esophageal motility disorder that affects both sexes and all ages. Peroral endoscopic myotomy (POEM) has been reported as an optional treatment since 2010 [1]. Frequently associated adverse events include pneumoperitoneum, pneumomediastinum, and pneumothorax, which are usually asymptomatic and managed conservatively [2, 3]. Perforation, bleeding, mediastinitis, and peritonitis rarely occur and are often symptomatic. Mucosal injuries (including dehiscence, ulcer, and ischemia) do not alter the post-procedural course [4]. A 31-year-old man, affected by idiopathic achalasia, was admitted as an outpatient to our Gastroenterological Unit owing to symptom recurrence and weight loss (Eckardt score 8). Two years before, he had undergone POEM, which was complicated by pneumomediastinum and ischemic damage of the distal esophagus with residual fibrosis. An esophagogram revealed a dilated esophagus (maximum diameter 60mm) and supracardial stricture extending 15 mm above. His dysphagia was most likely worsened by post-POEM complications. We planned to place a fully covered removable metal stent (SEMS; 60 × 27mm) to achieve progressive, effective dilation of the distal esophagus . The SEMS would be firmly fixed by means of an over-the-scope (OTS) clip. This novel OTS clip device has demonstrated success in reducing SEMS migration even in benign diseases [5]. The SEMS was released 10mm above the post-POEM stricture, 25 mm above the cardia, and fixed by means of the OTS clip. The patient was discharged uneventfully on the same day. An alternative approach (Heller myotomy) was ready to be employed in case of failure. At the 4-week follow-up, dysphagia had improved and the patient had gained weight. Both the OTS clip and the SEMS were removed using the remOVE device (Ovesco Endoscopy AG, Tübingen, Germany) . The patient was discharged uneventfully 12 hours later. After a further 4 weeks, an esophagogram revealed a significant reduction in the esophagus dilation and the patient’s clinical condition had significantly improved (Eckardt score 0)

Study of Galactic Cosmic-Ray Flux Modulation by Interplanetary Plasma Structures for the Evaluation of Space Instrument Performance and Space Weather Science Investigations

The role of high-energy particles in limiting the performance of on-board instruments was studied for the European Space Agency (ESA) Laser Interferometer Space Antenna (LISA) Pathfinder (LPF) and ESA/National Astronautics and Space Administration Solar Orbiter missions. Particle detectors (PD) placed on board the LPF spacecraft allowed for testing the reliability of pre-launch predictions of galactic cosmic-ray (GCR) energy spectra and for studying the modulation of proton and helium overall flux above 70 MeV n − 1 on a day-by-day basis. GCR flux variations up to approximately 15% in less than a month were observed with LPF orbiting around the Lagrange point L1 between 2016 and 2017. These variations appeared barely detected or undetected in neutron monitors. In this work the LPF data and contemporaneous observations carried out with the magnetic spectrometer AMS-02 experiment are considered to show the effects of GCR flux short-term variations with respect to monthly averaged measurements. Moreover, it is shown that subsequent large-scale interplanetary structures cause a continuous modulation of GCR fluxes. As a result, small Forbush decreases cannot be considered good proxies for the transit of interplanetary coronal mass ejections and for geomagnetic storm forecasting

RISC-V-Based Platforms for HPC: Analyzing Non-functional Properties for Future HPC and Big-Data Clusters

High-Performance Computing (HPC) have evolved to be used to perform simulations of systems where physical experimentation is prohibitively impractical, expensive, or dangerous. This paper provides a general overview and showcases the analysis of non-functional properties in RISC-V-based platforms for HPCs. In particular, our analyses target the evaluation of power and energy control, thermal management, and reliability assessment of promising systems, structures, and technologies devised for current and future generation of HPC machines. The main set of design methodologies and technologies developed within the activities of the Future and HPC & Big Data spoke of the National Centre of HPC, Big Data and Quantum Computing project are described along with the description of the testbed for experimenting two-phase cooling approaches