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Compiling Chapel: Keys to Making Parallel programming Productive at Scale 20

Compiling Chapel: Keys to Making Parallel Programming Produc...

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ACM International conference on Parallel architectures and Compilation Techniques (PACT)

作者： Chamberlain, Bradford L. Hewlett Packard Enterprise Seattle WA 98164 USA

ISBN: (纸本)9781450380751

Chapel is a parallel language designed to support productive programming from laptops to supercomputers. Unlike typical general-purpose approaches to large-scale computing, Chapel supports a global namespace and a global view of control. These make programming at scale more productive and natural by avoiding the need to utilize a Single Program, Multiple Data (SPMD) approach. Chapel is being developed as portable, open-source software and has demonstrated its ability to match or beat C/C++/MPI/openMP performance using code that's as easy to read as Python or Swift. In this talk, I will introduce some of Chapel's key features for those who are new to the language. However, most of the talk will focus on unique aspects of compiling Chapel. I will illustrate the transformations and analyses we use to implement Chapel's global view of data and control. I will also describe some optimizations that make use of Chapel's feature set to improve performance without sacrificing ease-of-use. In doing so, I will argue that when designed well, a productive language can enhance a compiler's ability to achieve performance and scalability rather than thwarting it. I'll wrap up by touching on some upcoming challenges for the Chapel compiler, including code generation for GPUs, reducing compilation time, and supporting interactive programming.

关键词： Chapel High Performance Computing Software Productivity

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ONet - A Temporal Meta Embedding network for MOOC Dropout Prediction 8

ONet - A Temporal Meta Embedding Network for MOOC Dropout Pr...

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8th ieee International conference on Big Data (Big Data)

作者： Pulikottil, Siby Charley Gupta, Manish Int Inst Informat Technol Bangalore IIIT B Bangalore Karnataka India

ISBN: (纸本)9781728162515

While massive open online courses (MOOCs) represent a promising approach to support education for all, their effectiveness is limited by high dropout rates. Based on the analysis that dropout is deeply correlated with the interaction patterns of a user, this paper proposes an attention meta embedding based deep temporal network to predict user dropout in MOOCs. The attention meta embedding gives an attention based weighted representation of different candidate embeddings and temporal modeling is done by Bi-GRU. An experimental evaluation of our solution on the KDDCUP 2015 and XuetangX datasets shows better results (AUC and F1 score) compared to both handcrafted feature techniques and all but one of the auto feature generated techniques. We obtain comparable results to the best previous method, but without having to use different architectures for different datasets.

关键词： MOOC Dropout Prediction Temporal GRU Attention

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QoE-DASH: DASH QoE Performance Evaluation Tool for Edge-Cache and Recommendation

QoE-DASH: DASH QoE Performance Evaluation Tool for Edge-Cach...

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ieee International conference on Communications (ICC)

作者： Joã o Paulo Esper Ana Claudia Bastos Loureiro Monç ã o Karlla B. Chaves Rodrigues Cristiano Bonato Both Sand Luz Corrê a Kleber Vieira Cardoso Universidade Federal de Goi&#x00E1 s Brazil University of Vale do Rio dos Sinos Brazil

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683484

The converging ecosystem provided by Multi-access Edge Computing (MEC) has motivated novel DASH video streaming provisioning scenarios involving the joint coordination of different mechanisms for caching, communication and control. Given the complexity of designing such mechanisms, it is important to provide the research community with open-source tools that support the assessment of their feasibility, specially in real-world environment. Current network emulators still require a significant programming effort to meeting this need. To fill this gap, a new DASH emulator called QoE-DASH is presented in this work. QoE-DASH builds upon goDASH to evaluate the QoE of users consuming DASH content, taking into account network properties, user preferences, and context information. To demonstrate the capabilities of QoE-DASH, we exercise different functionalities of our tool and present a case study where two joint caching and recommendation models, proposed in the literature, are evaluated and their effects on user QoE are depicted using state-of-the-art QoE metrics.

关键词： Performance evaluation Multi-access edge computing conferences Emulation Ecosystems Streaming media programming

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Automatic Mapping and Optimization to Kokkos with Polyhedral Compilation

Automatic Mapping and Optimization to Kokkos with Polyhedral...

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ieee High Performance Extreme Computing conference (HPEC)

作者： Baskaran, Muthu Jin, Charles Meister, Benoit Springer, Jonathan Reservoir Labs New York NY 10012 USA MIT Cambridge MA 02139 USA

ISBN: (纸本)9781728192192

In the post-Moore's Law era, the quest for exascale computing has resulted in diverse hardware architecture trends, including novel custom and/or specialized processors to accelerate the systems, asynchronous or self-timed computing cores, and near-memory computing architectures. To contend with such heterogeneous and complex hardware targets, there have been advanced software solutions in the form of new programming models and runtimes. However, using these advanced programming models poses productivity and performance portability challenges. This work takes a significant step towards addressing the performance, productivity, and performance portability challenges faced by the high-performance computing and exascale community. We present an automatic mapping and optimization framework that takes sequential code and automatically generates high-performance parallel code in Kokkos, a performance portable parallel programming model targeted for exascale computing. We demonstrate the productivity and performance benefits of optimized mapping to Kokkos using kernels from a critical application project on climate modeling, the Energy Exascale Earth System Model (E3SM) project. This work thus shows that automatic generation of Kokkos code enhances the productivity of application developers and enables them to fully utilize the benefits of a programming model such as Kokkos.

关键词： Compiler mapping exascale programming models Kokkos E3SM application

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Development of open-Source, Edge Energy Management System for Tactical Power networks

Development of Open-Source, Edge Energy Management System fo...

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ieee/ACM International Symposium on Big Data Computing (BDC)

作者： Syed Wali Irfan Khan Yasir Ali Farrukh Muhammad Areeb Fasih Muhammad Hassan Ul Haq Majida Kazmi Department of Electrical and Computer Engineering Texas A&M University College Station TX USA Department of Electrical Engineering NED University of Engineering and Technology Karachi Pakistan

Microgrids specialized for tactical operations have been subjected to several challenges. These tactical power networks are islanded and have a relatively low power generation capacity. Meeting power requirements of military equipment, having intermittent and highly inductive nature, exposes microgrids to severe stresses. Existing methodologies to monitor and control the impact of load variations require sophisticated equipment and trained personnel. The objective of this research paper is to present an open-source edge energy monitoring system (EEMS) for efficient demand management of tactical networks. The proposed system is capable of capturing all minute operational artifacts, including harmonic distortions and power quality of these networks. A variable gain amplifier circuit enables the proposed EMS to sense all the signals in a wide range of power with higher resolution. The proposed system utilizes raspberry pi as an edge device to meet the low power requirements of tactical networks. The novel concurrent programming approach adopted in the proposed EMS, effectively handles the large amount of data acquired from the network. This parallel processing of acquired data speeds up the execution process. All electrical parameters obtained during this process are stored in an encrypted local database that can be utilized for fault analysis and load prediction. Further integration of machine learning tools in proposed EMS assists in automated power network reconfiguration and tuning under harsh battlefield situations.

关键词： Power quality Microgrids programming Parallel processing Personnel Monitoring Tuning

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CCTV based system for detection of anti-virus masks 24

CCTV based system for detection of anti-virus masks

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24th ieee conference on Signal Processing: Algorithms, architectures, Arrangements, and Applications (ieee SPA)

作者： Podbucki, Kacper Suder, Jakub Marciniak, Tomasz Dabrowski, Adam Poznan Univ Tech Fac Control Robot & Elect Engn Inst Automat Control & Robot Div Elect Syst & Signal Proc Jana Pawla II 24 PL-60965 Poznan Poland

ISBN: (纸本)9788362065394

This paper presents the use of neural networks to detect people with anti-virus masks. The algorithm allows to determine if a person has a correctly worn mask (covered nose and mouth). The use of neural networks has been compared with typical Haar cascade frontal face solutions available in the openCV library. The proposed solution has been checked for efficiency and precision, as well as for the minimum resolution requirements of the resulting facial image. The software works on still images as well as on video sequences from computer webcams and CCTV cameras.

关键词： COVID-19 neural networks convolutional neural networks anti-virus masks mask detection vision system openCV Python programming

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Challenges Towards Automation of Live Telco network Management: Closed Control Loops 16

Challenges Towards Automation of Live Telco Network Manageme...

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16th International conference on network and Service Management (CNSM) / 2nd International Workshop on Analytics for Service and Application Management (AnServApp) / 1st International Workshop on the Future Evolution of Internet Protocols (IPFuture)

作者： Vaishnavi, Ishan Ciavaglia, Laurent Lenovo Deutshcland GmbH Munich Germany Nokia Paris France

ISBN: (纸本)9783903176317

Higher automation is seen as a key milestone in the evolution of telecom networks. Maintaining a myriad of different technologies over constantly evolving architectures (from 2G-5G) increases operational expenditures and poses real integration and deployment challenges for operators. In addition, the new network dynamism introduced with virtualization, eventually leading to multi-tenancy, will add further complexities for the operator in managing the network. This paper outlines the essential role of open and closed control loops in achieving higher levels of network automation, identifies the related challenges that operators face in deploying control loops in live environments and describes preliminary, standards-oriented solutions.

关键词： network management automation 5G and beyond Slicing Analytics Closed control loops

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Latency-aware and -predictable Communication with open Protocol Stacks for Remote Drone Control 16

Latency-aware and -predictable Communication with Open Proto...

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16th Annual International conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Boehmer, Marlene Schmidt, Andreas Pereira, Pablo Gil Herfet, Thorsten Saarland Informat Campus Telecommun Lab Saarbrucken Germany

ISBN: (纸本)9781728143514

In order to create cooperating swarms of Unmanned Autonomous Vehicles (UAVs) that also interact with various other systems and devices, open and free communication systems are mandatory. This paper presents an implementation of such a communication system to incorporate the Crazyflie nano-drone as a UAV platform. The protocol stack leverages the open Predictably Reliable Real-time Transport (PRRT) protocol that adds latency-awareness and-predictability to stacks composed of standard Internet protocols. To enable the drone to receive and reply to control commands via Wi-Fi, it has been extended with a Raspberry Pi that runs two variants of the Crazybridge-a software to connect the control board to the network. To evaluate how practical this solution is for the use in control applications, the communication has been analysed with a focus on the latency properties. Our investigations show that despite using the open protocol stack-and hence opting out of specialised implementations-the resulting latencies are in the same order of magnitude (4 to 9ms) as the latency of the proprietary link.

关键词： Communication architectures Communication Protocols Drone networks Latency Evaluation

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Budgeted Subset Selection for Fine-tuning Deep Learning architectures in Resource-Constrained Applications

Budgeted Subset Selection for Fine-tuning Deep Learning Arch...

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International Joint conference on Neural networks (IJCNN) held as part of the ieee World Congress on Computational Intelligence (ieee WCCI)

作者： Banerjee, Subhankar Chakraborty, Shayok Florida State Univ Dept Comp Sci Tallahassee FL 32306 USA

ISBN: (纸本)9781728169262

The growing success and popularity of deep learning in computer vision have resulted in the availability of several pre-trained deep learning architectures (such as AlexNet, ResNet, VGGNet among others). A common practice in deep learning research is to use one of the pre-trained models and fine-tune it to a given target task, using training data from the target. However, training a deep learning model efficiently necessitates expensive, high-quality GPUs and distributed computing infrastructures. Some applications (such as those running on mobile platforms) are severely limited in terms of memory and computational resources;in these applications, it is a significant challenge to fine-tune a pre-trained deep learning model to a target task, using large amounts of target training data. Cloud services can be leveraged for training, but involve issues with data privacy and cost. In such applications, it is important to select an informative subset of the training data and fine-tune the deep model using only the selected subset. In this paper, we propose a novel framework to address this problem. We pose subset selection as a constrained NP-hard integer quadratic programming problem and derive an efficient linear relaxation to select a subset of exemplar instances. Our extensive empirical studies on three challenging vision datasets (from different application domains) using three commonly used pre-trained deep learning models corroborate the potential of our framework for real-world, resource-constrained applications.

关键词： deep learning subset selection

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Tracking Performance Portability on the Yellow Brick Road to Exascale

Tracking Performance Portability on the Yellow Brick Road to...

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ieee/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)

作者： Deakin, Tom Poenaru, Andrei Lin, Tom McIntosh-Smith, Simon Univ Bristol Dept Comp Sci Bristol Avon England

ISBN: (纸本)9781665422871

With Exascale machines on our immediate horizon, there is a pressing need for applications to be made ready to best exploit these systems. However, there will be multiple paths to Exascale, with each system relying on processor and accelerator technologies from different vendors. As such, applications will be required to be portable between these different architectures, but it is also critical that they are efficient too. These double requirements for portability and efficiency begets the need for performance portability. In this study we survey the performance portability of different programming models, including the open standards openMP and SYCL, across the diverse landscape of Exascale and pre-Exascale processors from Intel, AMD, NVIDIA, Fujitsu, Marvell, and Amazon, together encompassing GPUs and CPUs based on both x86 and Arm architectures. We also take a historical view and analyse how performance portability has changed over the last year.

关键词： performance portability programming models

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