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processing Millions of Single Cells by SHARP 20

Processing Millions of Single Cells by SHARP

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11th ACM conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)

作者： Wan, Shibiao Kim, Junil Fan, Yiping Won, Kyoung Jae St Jude Childrens Res Hosp Ctr Appl Bioinformat 332 N Lauderdale St Memphis TN 38105 USA Univ Copenhagen Biotech Res & Innovat Ctr Copenhagen Denmark

ISBN: (纸本)9781450379649

Single-cell technologies have received extensive attention from bioinformatics and computational biology communities due to their evolutionary impacts on uncovering novel cell types and intra-population heterogeneity in various domains of biology and medicine. Recent advances on single-cell RNA-sequencing (scRNA-seq) technologies have enabled parallel transcriptomic profiling of millions of cells. However, existing scRNA-seq clustering methods are lack of scalability, time-consuming and prone to information loss during dimension reduction. To address these concerns, we present SHARP [1], an ensemble random projection-based algorithm which is scalable to clustering 10 million cells. By adopting a divide-and-conquer strategy, a sparse random projection and two-layer meta-clustering, SHARP has the following advantages: (1) hyper-faster than existing algorithms;(2) scalable to 10-million cells;(3) accurate in terms of clustering performance;(4) preserving cell-to-cell distance during dimension reduction;and (5) robust to dropouts in scRNA-seq data. Comprehensive benchmarking tests on 20 scRNA-seq datasets demonstrate SHARP remarkably outperforms state-of-the-art methods in terms of speed and accuracy. To the best of our knowledge, SHARP is the only R-based tool that is scalable to clustering 10 million cells. With an avalanche of single cells in different tissues to be sequenced in multiple international projects like the Human Cell Atlas, we believe SHARP will serve as one of the useful and important tools for large-scale single-cell data analysis. Several potential future directions include while keeping the scalability and speed of SHARP, how to extend its functions into rare cell type detection and integrating single cell data from different platforms, experiments and conditions.

关键词： Single cell analysis 10 million cells random projection dimension reduction clustering

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Reliability and Modelability Advantages of Distributed Switching for Reconfigurable 2D Processor Arrays

Reliability and Modelability Advantages of Distributed Switc...

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international conference and Workshop on Computing and Communication (IEMCON)

作者： Behrooz Parhami University of California Santa Barbara CA USA

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

Processor arrays have been used, either as the main computation engine or as special-purpose adjuncts, for a variety of applications requiring very high performance. As the size of such an array increases, the possibility of processor malfunctions, leading to loss of computational capabilities, can no longer be ignored. While many switching architectures and reconfiguration algorithms have been proposed for building processor arrays, modeling of their reliability has been inadequately addressed. In this paper, I study differences between 2D processor arrays with centralized and distributed switching, pointing to advantages of the latter in terms of reliability, regularity, modularity, and VLSI realizability. As important side results, I formulate the notions of reliability inversion (a less reliable system prevailing over a more reliable one due to modeling uncertainties) and modelability (the property of a system that makes it possible to derive tight reliability bounds, thus making reliability inversion less likely).

关键词： Uncertainty Systematics Two dimensional displays Switches parallel processing Very large scale integration Reliability engineering

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Efficient Non-uniform Channelization for SDR Using Frequency Domain Filtering

Efficient Non-uniform Channelization for SDR Using Frequency...

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2014 IEEE 5th international conference on Software Engineering and Service Science

作者： Tian-li Jiang Ke-xian Gong Hua Peng Di Wu Institute of Information Systems Engineering Information Engineering University

An arbitrary sampling rate conversion algorithm based on frequency domain filtering(FDF-ASRC) is *** number of Fourier coefficients in FDF-ASRC is irrelevant to the symbol rate of interested *** the resampling algorithm to non-uniform channelization,a few modules of Fourier transform(FT) and inverse Fourier transform(IFT) can guarantee infinite channels in ***,the sampling rate of output signal can be adjusted to an integer multiple of symbol rate,which can be passed to demodulator *** comparison with seven architectures of non-uniform channelizers,the computational complexity of the proposed channelizers is equal to the best.

关键词： SD Non-uniform channelization Multi-rate signal processing Arbitrary sampling rate conversion Frequency domain filtering

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Offline Imitation Learning Using Reward-free Exploratory Data 22

Offline Imitation Learning Using Reward-free Exploratory Dat...

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Proceedings of the 2022 5th international conference on algorithms, Computing and Artificial Intelligence

作者： Hao Wang Dawei Feng Bo Ding Wei Li College of Computer National University of Defense Technology China National Laboratory for Parallel and Distributed Processing National University of Defense Technology China Independent Researcher China

ISBN: (纸本)9781450398336

Offline imitative learning(OIL) is often used to solve complex continuous decision-making tasks. For these tasks such as robot control, automatic driving and etc., it is either difficult to design an effective reward for learning or very expensive and time-consuming for agents to collect data interactively with the environment. However, the data used in previous OIL methods are all gathered by reinforcement learning algorithms guided by task-specific rewards, which is not a true reward-free premise and still suffers from the problem of designing an effective reward function in real tasks. To this end, we propose the reward-free exploratory data driven offline imitation learning (ExDOIL) framework. ExDOIL first trains an unsupervised reinforcement learning agent by interacting with the environment, and collects enough unsupervised exploration data during training; then, a task independent yet simple and efficient reward function is used to relabel the collected data; Finally, an agent is trained to imitate the expert to complete the task through a conventional RL algorithm such as TD3. Extensive experiments on continuous control tasks demonstrate that the proposed framework can achieve better imitation performance(28% higher episode returns on average) comparing with previous SOTA method(ORIL) without any task-specific rewards.

关键词： dataset

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Efficient parallel Process Migration Algorithm Using Statistical Approach 4th

Efficient Parallel Process Migration Algorithm Using Statist...

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international conference on Computational Intelligence and Communication Networks

作者： Chandu D. Vaidya M. B. Chandak M-Tech (4th SEM) Nagpur India

ISBN: (纸本)9781467329811

the cost or complexity of serial algorithms is estimated in terms of the space i.e. memory and time i.e. processor cycle. parallel algorithms need to optimize one or more resources and also the communication between different processors. parallel processing involves a technique by which complex data sets are broken into individual threads and processed simultaneously on one or more cores. If a system is doing one task which consists of large computation, it will take more time to finish that task. the proposed approach enables the efficient exploitation of parallelism by well-balanced distribution of workload to host processors and minimizes the overhead on single computer. Data division and migration is used for parallel processing. But if the process is migrated, it needs to take care of process for execution like pause, resume etc. It also needs to set check points for processes that become very complicated and time consuming. the proposed work divides the task into some subset on the basis of global decision and migrate that task among the slave computers. the output from the slave computers are collected on the master node. the proposed work considers the SIMD and MIMD computer applications for comparing the result for analysis. the proposed work contains static approach for process migration using data level parallelism. It creates small chunks of data from the large data set to reduce the execution time. It considers the memory availability of the slave nodes for taking the decision of data transfer. the proposed approach considers equal and unequal data division and distribution for load balancing. In addition to computational cost, the cost of memory accesses is an important factor for determining program performance. Proposed work is based on memory availability of slave nodes, as per their availability they are given an additional task to perform.

关键词： Component parallel processing Load balancing Cluster computing Process migration

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A Locality-Preserving Write Buffer Design for Page-Mapping Multichannel SSDs

A Locality-Preserving Write Buffer Design for Page-Mapping M...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Sheng Min Huang Li Pin Chang Department of Computer Science National Chiao-Tung University Taiwan

ISBN: (纸本)9781479961245

Advanced SSDs employ a RAM-based write buffer to improve their write performance. the buffer intentionally delays write requests in order to reduce flash write traffic and reorders them to minimize the cost of garbage collection. this work presents a novel buffer algorithm for page-mapping multichannel SSDs. We propose grouping temporally or spatially correlated buffer pages and writing these grouped buffer pages to the same flash block. this strategy dramatically increases the probability of bulk data invalidations in flash blocks. In multichannel architectures, channels are assigned to their own groups of buffer pages for writing, and so channel striping does not divide a group of correlated buffer pages into small pieces. We have conducted simulations and experiments using a SSD simulator and a real SSD platform, respectively. Our results show that our design greatly outperforms existing buffer algorithms.

关键词： Ash Writing Buffer storage Algorithm design and analysis parallel processing Heuristic algorithms Correlation

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A new efficient algorithm for generating the scrambled Sobol’ sequence

A new efficient algorithm for generating the scrambled Sobol...

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5th international conference on Numerical Methods and Applications, NMA 2002

作者： Atanassov, Emanouil I. Central Laboratory for Parallel Processing Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (纸本)3540006087

the Sobol’ sequence is the most widely deployed low-discrepancy sequence, and is used for calculating multi-dimensional integrals and in quasi-Monte Carlo simulation. Owen first proposed the idea of scrambling this sequence in a manner that maintained its low discrepancy. One of his motivations was to use these scrambled sequences to provide quasi-Monte Carlo methods with simple error estimates like those in normal Monte Carlo. In fact, it is now common for the Sobol’ sequence as well as (t, m, s)-nets and (t, s)-sequences to be used with scrambling. However, many have pointed out that scrambling is often difficult to implement and time consuming. In this paper we describe a new generation algorithm that allows consecutive terms of the scrambled Sobol’ sequence to be obtained with essentially only two operations per coordinate: one floating point addition and one bit-wise xor operation. Note: this omits operations that are needed only once per tuple. this scrambling is achieved at no additional computational cost over that of unscrambled generation as it is accomplished totally in the initialization. In addition, the terms of the sequence are obtained in their normal order, without the usual permutation introduced by Gray code ordering used to minimize the cost of computing the next Sobol’ element. this algorithm is relatively simple and is quite suitable for parallelization and vectorization. An example implementation of the algorithm, written in pseudo-code is presented. Possible improvements of the algorithm are discussed along with the presentation of some timing results. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Monte Carlo methods

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Solving Motion Law by Numerical Simulation on Bowl Seeding Transplanting Robot

Solving Motion Law by Numerical Simulation on Bowl Seeding T...

引用

Computer and Computing Technologies in Agriculture V——5th IFIP TC 5/SIG 5.1 conference(CCTA 2011) Part Ⅲ

作者： Chunhui Qi Jianping Hu Jun Ma Jianbing Zhang Key Laboratory of Modern Agricultural Equipment and Technology Ministry of Education & Jiangsu ProvinceJiangsu UniversityHigh-tech Key Laboratory of Agricultural Equipment & Intelligentization of Jiangsu Province

ISBN: (纸本)9783642272745

the paper using the inverse kinematics theory of the parallel mechanism,studied the movable needs of the transplanting *** the inverse kinematics formula of transplanting *** the demand of the "fetch and plant" operations,made an important research on the two trajectory planning methods of the moving platform:quintic and septic polynomial motion laws,acquired their variation rules of displacement,velocity,acceleration and saltus by using matlab software,and to make *** selected the law of motion equation,through numerical simulation of inverse kinematics by matlab,acquired kinematic parameters angular speed and acceleration of the two active motors,can be used as the priority basis for control the movement of the manipulator.

关键词： parallel mechanism transplanting bowl seeding trajectory planning inverse position numerical simulation

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Improving Carbon Emission Predictions with NLP and LSTM Integration

Improving Carbon Emission Predictions with NLP and LSTM Inte...

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Information Science, parallel and Distributed Systems (ISPDS), international conference on

作者： Shuang Guo Junfei Chen Business School Hohai University Nanjing China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

In recent years, the urgency of addressing climate change has intensified, necessitating accurate predictions of carbon emissions to inform policy decisions and mitigation strategies. this paper presents an innovative approach to improving carbon emission prediction models by integrating Natural Language processing (NLP) techniques with Long Short-Term Memory (LSTM) networks. Initially, a baseline LSTM model is developed to forecast carbon emissions using historical emission data. Subsequently, we incorporate NLP-processed information extracted from relevant textual sources such as government reports, news articles, and scientific papers. Key features, including keywords, thematic distributions, and sentiment scores, are derived from the text and combined with numerical data to create a multi modal input for the LSTM model. Experimental results demonstrate that the inclusion of NLP-enhanced features significantly enhances the model’s predictive accuracy. this study underscores the potential of leveraging textual data to enrich traditional prediction models, providing a more comprehensive tool for understanding and forecasting carbon emission trends.

关键词： Accuracy Government Carbon dioxide Predictive models Feature extraction Natural language processing Data models

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SPAMeR: Speculative Push for Anticipated Message Requests in Multi-Core Systems 22

SPAMeR: Speculative Push for Anticipated Message Requests in...

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Proceedings of the 51st international conference on parallel processing

作者： Qinzhe Wu Ashen Ekanayake Ruihao Li Jonathan Beard Lizy John University of Texas at Austin United States of America Arm United States of America

ISBN: (纸本)9781450397339

With increasing core counts and multiple levels of cache memories, scaling multi-threaded and task-level parallel workloads is continuously becoming a challenge. A key challenge to scaling the number of communicating tasks (or threads) is the rate at which existing communication mechanisms scale (in terms of latency and bandwidth). architectures with hardware accelerated queuing operations have the potential to reduce the latency and improve scalability of moving data between processing elements, reducing synchronization penalties, and thereby improving the performance of task-level parallel workloads. While hardware queues reduce synchronization penalties, they cannot fully hide load-to-use latency, i.e., perfect pipelines often are not realized. there is the potential, however, for better overlap. If the inter-processor communication latency is equal to or less than the time spent processing a message at the consumer, any and all latency may be overlapped while the consumer is processing. We exploit this property to speedup parallel applications above and beyond existing hardware queues. In this paper, we present SPAMeR, a speculation mechanism built on top of a state-of-the-art hardware-driven message queue architecture. SPAMeR has the capability to speculatively push messages in anticipation of consumer message requests. Unlike pre-fetch approaches which predict what addresses to fetch next, with a queue we know exactly what data is needed next but not when it is needed; SPAMeR adds algorithms that attempt to predict this. We evaluate the effectiveness of SPAMeR with a set of diverse task-parallel benchmarks utilizing the gem5 full system simulator, and observe a 1.33 × average speedup.

关键词： parallel computing message queue multi-core system speculation

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