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检索条件"任意字段=9th International Conference on Algorithms and Architectures for Parallel Processing"

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Efficient Implementation of Camera Mirror System Algorithm on Heterogeneous Chip architectures 9

Efficient Implementation of Camera Mirror System Algorithm o...

引用

9th IEEE international conference on Consumer Electronics (ICCE-Berlin)

作者： Milosevic, Marko Isic, Vesna Bjelica, Milan Z. Andjelic, Tihomir Univ Novi Sad Fac Tech Sci Novi Sad Serbia RT RK Inst Comp Based Syst Novi Sad Serbia

ISBN: (纸本)9781728127453

Advanced Driving Assistance Systems (ADAS) are vehicle-based intelligent safety systems which help the drivers to improve safety driving. One important building block of ADAS is a Camera Mirror System (CMS). CMS provides means to enhance rearview mirrors by digital information, such as detected obstacles, collision avoidance alerts and more. Efficient implementation of CMS requires the utilization of dedicated processing in hardware, to ensure minimal latency and coexistence with other algorithms in heterogeneous hardware environments. In this paper we analyze CMS algorithm data pipeline and provide insights on how each phase can be efficiently accelerated using dedicated hardware blocks on present-day high-performance microcontrollers. We give early evaluation of the presented approach on top of two architectures: TI TDA2x and NVIDIA Xavier.

关键词： automotive software heterogeneous chip architecture ADAS Camera Mirror System

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Mask-Predict: parallel Decoding of Conditional Masked Language Models 9

Mask-Predict: Parallel Decoding of Conditional Masked Langua...

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conference on Empirical Methods in Natural Language processing / 9th international Joint conference on Natural Language processing (EMNLP-IJCNLP)

作者： Ghazvininejad, Marjan Levy, Omer Liu, Yinhan Zettlemoyer, Luke Facebook AI Res Seattle WA 98101 USA

ISBN: (纸本)9781950737901

Most machine translation systems generate text autoregressively from left to right. We, instead, use a masked language modeling objective to train a model to predict any subset of the target words, conditioned on both the input text and a partially masked target translation. this approach allows for efficient iterative decoding, where we first predict all of the target words non-autoregressively, and then repeatedly mask out and regenerate the subset of words that the model is least confident about. By applying this strategy for a constant number of iterations, our model improves state-of-the-art performance levels for non-autoregressive and parallel decoding translation models by over 4 BLEU on average. It is also able to reach within about 1 BLEU point of a typical left-to-right transformer model, while decoding significantly faster.(1)

关键词： Iterative decoding

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DIRECT DIGITIZATION AND ADC PARAMETER TRADE-OFF FOR BUNCH-BY-BUNCH SIGNAL processing 9

DIRECT DIGITIZATION AND ADC PARAMETER TRADE-OFF FOR BUNCH-BY...

引用

9th international Beam Instrumentation conference, IBIC 2020

作者： Degl'Innocenti, I. Boccardi, A. Wendt, M. Fanucci, L. CERN Geneva Switzerland Department of Information Engineering Università di Pisa Pisa Italy

ISBN: (纸本)9783954502226

With the technology improvements of analog-to-digital converters in terms of sampling rate and achievable resolution, direct digitization of beam signals is of growing interest in the field of beam diagnostics. the selection of a state-of-the-art analog-to-digital converter for such a task imposes a trade-off between sampling frequency and resolution. Understanding the dependency of the system performance on these features is fundamental. this paper presents an analysis and design methodology for such architectures. Analytical tools are used to guide the designer and to estimate the system performance as a function of the analog-to-digital converter performance. these estimations are then validated by Monte-Carlo simulations. As an example of this methodology an analysis for the next-generation electronics of the Large Hadron Collider beam position monitoring system is presented. the analytical model and the results obtained are discussed, along with comparisons to beam measurements obtained at the Large Hadron Collider. © IBIC *** rights reserved

关键词： Monte Carlo methods

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Development Environment for Hybrid Applications on Heterogeneous Clusters 9

Development Environment for Hybrid Applications on Heterogen...

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IEEE 9th international conference on Advanced Computing (IACC)

作者： Deepika, H., V Mangala, N. C DAC Syst Software HPC Bangalore Karnataka India

ISBN: (纸本)9781728143927

the evolution of cluster computers based on multicores, many cores and GPGPU accelerators is encouraging application developers to write hybrid parallel programs. Hybrid parallel programming is quite complex as it requires use of multiple programming paradigms such as MPI, OperiMP, CTIDA/OpenCL to exploit the varied computational power available in a system. the paper brings out the challenges faced by application developers desiring to use heterogeneous HPC clusters. It describes a unified development environment which eases the complete development lifecycle of hybrid parallel programs on a HPC cluster. the software is capable of providing access to multiple clusters of different architectures, owing to the modularity of design and web based approach. the paper also serves as a good resource for researchers interested to gain an insight into hybrid parallel programming.

关键词： Hybrid parallel programming Heterogeneous CPU-GPU architecture Integrated Development Environment petascale prograntnting programmer productivity

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Experimental Study on Neural Network-ARX and ARMAX Actuation Identification of a 3-DoF Delta parallel Robot for Accurate Motion Controller Design

Experimental Study on Neural Network-ARX and ARMAX Actuation...

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RSI/ISM international conference on Robotics and Mechatronics (ICROM)

作者： Saeed Rahimi Hasan Jalali Mohammad Reza Hairi Yazdi Ahmad Kalhor Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Mechanical Engineering University of Tehran Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Mechanical Engineering College of Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781665420952

this paper investigates the problem of actuator identification of a 3-DoF Delta parallel robot, by means of linear AutoRegressive Moving Average with eXogenous input (ARMAX) and nonlinear dynamic Neural Network AutoRegressive with eXogenous input (NN-ARX) methods. To this end, the ARMAX and NN-ARX approaches are used to develop a scheme which is capable of identifying a model for each actuator. Based on the ARMAX structure, an accurate model of the actuation system is derived. the model is then trained and tested using the data collected from a real robotic setup. Using a dynamic neural network capabilities, an identification and prediction scheme is designed for modeling the nonlinear dynamic behavior of the system. the NN-ARX is trained based on the collected data from the system, and the new trajectory data is used to validate both methods. By considering the results of experimental implementations, three servo motors are demonstrated to have different dynamical behavior which was expected to happen from the outset, due to uncertainty in fabrication of motors component and gearbox. In the identification and prediction stages, the Root Mean Square Errors (RMSE) index is used to validate and analyze the performance of each method using the validation data from new trajectories. In terms of predicting the output of the system, NN-ARX performed better than ARMAX with RMSE of 0.001441, compared to ARMAX with RMSE of 0.0886. Due to the high accuracy of the obtained models. thus they can be used in the design of motion controllers and modelling disturbances in the system.

关键词： Actuators parallel robots Artificial neural networks Predictive models Mathematical models Trajectory Nonlinear dynamical systems

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Deep Transfer Learning for Subject-Independent ERP-based BCIs

Deep Transfer Learning for Subject-Independent ERP-based BCI...

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international Winter Workshop on Brain-Computer Interface (BCI)

作者： Kassymzhomart Kunanbayev Dias Azhigulov Berdakh Abibullaev Amin Zollanvari School of Engineering and Digital Sciences Nazarbayev University Kazakhstan

ISBN: (数字)9781728184852

ISBN: (纸本)9781728184869

Designing subject-independent Brain-Computer Interfaces remains to be an open question for developing systems that can capture the inter-subject intrinsic brain features and classify them with reasonable accuracy. this paper presents the application of the state-of-the-art deep transfer learning architectures on classifying ERP signals. We report 66.87%, 67.64%, 65.58%, and 71.93% test classification accuracy for DenseNet121, DenseNet201, Xception, and VGG-16 models, respectively. the experimental results demonstrate the viability of our approach in subject independent ERP-signals classification and suggest the better performance of models with fewer layers in classifying ERP signals.

关键词： Transfer learning Signal processing Brain modeling Brain-computer interfaces Biological neural networks

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parallel Stateful Logic in RRAM: theoretical Analysis and Arithmetic Design 30

Parallel Stateful Logic in RRAM: Theoretical Analysis and Ar...

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30th IEEE international conference on Application-Specific Systems, architectures and Processors (ASAP)

作者： Wang, Feng Luo, Guojie Sun, Guangyu Zhang, Jiaxi Huang, Peng Kang, Jinfeng Peking Univ Ctr Energy Efficient Comp & Applicat Beijing Peoples R China Peking Univ Inst Microelect Beijing Peoples R China

ISBN: (纸本)9781728116013

processing-in-memory (PIM) provides massive parallelism with high energy efficiency and becomes a promising solution to the "memory wall" problem. Recently, the emerging metal-oxide resistive random access memory (RRAM) has shown its potential to design a PIM architecture. Several stateful logic operations, e.g., NOR and NAND, can be executed in parallel in an RRAM crossbar. Although previous works have designed some algorithms using the stateful logic, it is still under exploration how to fully exploit its potential high parallelism and design an asymptotically fast algorithm for a given function. In this work, we theoretically analyze the parallelism in an RRAM crossbar and design several asymptotically optimal arithmetic algorithms. In detail, we first propose the Single Instruction Multiple Lines (SIML) model to unify the stateful logic families and prove three lower bounds on the time complexity of a parallel RRAM algorithm. then, we design three algorithms for integer addition functions with the stateful logic, guided by the lower bound analysis. All of them reach the time complexity lower bound. Finally, We make two extensions of the integer addition algorithms, supporting multiplication functions by decomposing them to additions and supporting the flex-point data type by proposing an exponent and mantissa update flow. Experimental evaluation shows that our integer algorithms achieves a speedup up to 13.79x over the previous RRAM algorithms. Our flex-point implementation achieves a 26.60x speedup and saves 73.68% energy compared to an ARM.

关键词： Time complexity Computer architecture parallel processing Computational modeling Resistance Switches Random access memory

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Neural data-to-text generation: A comparison between pipeline and end-to-end architectures 9

Neural data-to-text generation: A comparison between pipelin...

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conference on Empirical Methods in Natural Language processing / 9th international Joint conference on Natural Language processing (EMNLP-IJCNLP)

作者： Ferreira, thiago Castro van der Lee, Chris van Miltenburg, Emiel Krahmer, Emiel Tilburg Univ Tilburg Ctr Cognit & Commun TiCC Tilburg Netherlands Fed Univ Minas Gerais UFMG Belo Horizonte MG Brazil

ISBN: (纸本)9781950737901

Traditionally, most data-to-text applications have been designed using a modular pipeline architecture, in which non-linguistic input data is converted into natural language through several intermediate transformations. By contrast, recent neural models for data-to-text generation have been proposed as end-to-end approaches, where the non-linguistic input is rendered in natural language with much less explicit intermediate representations in between. this study introduces a systematic comparison between neural pipeline and end-to-end data-to-text approaches for the generation of text from RDF triples. Both architectures were implemented making use of the encoder-decoder Gated-Recurrent Units (GRU) and Transformer, two state-of-the art deep learning methods. Automatic and human evaluations together with a qualitative analysis suggest that having explicit intermediate steps in the generation process results in better texts than the ones generated by end-to-end approaches. Moreover, the pipeline models generalize better to unseen inputs. Data and code are publicly available.(1)

关键词： Pipelines

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parallel Searching on Biological Networks 27

Parallel Searching on Biological Networks

引用

27th Euromicro international conference on parallel, Distributed and Network-Based processing (PDP)

作者： Bombieri, Nicola Bonnici, Vincenzo Giugno, Rosalba Univ Verona Dipartimento Informat Strata Grazie 15 I-37134 Verona Italy

ISBN: (纸本)9781728116440

Software applications for biological networks analysis rely on graphs to model the structure interactions. A great part of them requires searching for subgraphs in a target graph or in collections of graphs. Even though very efficient algorithms have been defined to solve such a subgraph isomorphisms problem, the complexity of current real biological networks make their sequential execution time prohibitive. On the other hand, parallel architectures, from multi-core to many-core, have become pervasive to deal with the problem of the data size. Nevertheless, the sequential nature of the graph searching algorithms makes their implementation for parallel architectures very challenging. this paper presents three different parallel solutions for the graph searching problem. the first two target the exact search for multi-core CPUs and many-core GPUs, respectively. the third one targets the approximate search for GPUs, which handles node, edge, and node label mismatches. the paper shows how different techniques have been developed in all the solutions to reduce the search space complexity. the paper shows the performance of the proposed solutions on representative biological networks containing antiviral chemical compounds and protein interactions networks.

关键词： Biology Search problems Complexity theory Graphics processing units Indexes Topology

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parallel Iterative Edit Models for Local Sequence Transduction 9

Parallel Iterative Edit Models for Local Sequence Transducti...

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conference on Empirical Methods in Natural Language processing / 9th international Joint conference on Natural Language processing (EMNLP-IJCNLP)

作者： Awasthi, Abhijeet Sarawagi, Sunita Goyal, Rasna Ghosh, Sabyasachi Piratla, Vihari Indian Inst Technol Dept Comp Sci & Engn Mumbai Maharashtra India

ISBN: (纸本)9781950737901

We present a parallel Iterative Edit (PIE) model for the problem of local sequence transduction arising in tasks like Grammatical error correction (GEC). Recent approaches are based on the popular encoder-decoder (ED) model for sequence to sequence learning. the ED model auto-regressively captures full dependency among output tokens but is slow due to sequential decoding. the PIE model does parallel decoding, giving up the advantage of modelling full dependency in the output, yet it achieves accuracy competitive with the ED model for four reasons: 1. predicting edits instead of tokens, 2. labeling sequences instead of generating sequences, 3. iteratively refining predictions to capture dependencies, and 4. factorizing logits over edits and their token argument to harness pretrained language models like BERT. Experiments on tasks spanning GEC, OCR correction and spell correction demonstrate that the PIE model is an accurate and significantly faster alternative for local sequence transduction.

关键词： Error correction

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