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SRLGRN: Semantic Role Labeling Graph Reasoning Network
This work deals with the challenge of learning and reasoning over multi-...
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Cross-Modality Relevance for Reasoning on Language and Vision
This work deals with the challenge of learning and reasoning over langua...
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Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking
In edge computing scenarios, the distribution of data and collaboration ...
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RLTM: An Efficient Neural IR Framework for Long Documents
Deep neural networks have achieved significant improvements in informati...
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XOS: An Application-Defined Operating System for Data Center Servers
Rapid growth of datacenter (DC) scale, urgency of cost control, increasi...
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Enhanced Quasi-Maximum Likelihood Decoding of Short LDPC Codes based on Saturation
In this paper, we propose an enhanced quasi-maximum likelihood (EQML) de...
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Data Motif-based Proxy Benchmarks for Big Data and AI Workloads
For the architecture community, reasonable simulation time is a strong r...
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Data Motifs: A Lens Towards Fully Understanding Big Data and AI Workloads
The complexity and diversity of big data and AI workloads make understan...
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BigDataBench: A Scalable and Unified Big Data and AI Benchmark Suite
Several fundamental changes in technology indicate domain-specific hardw...
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BigDataBench: A Dwarf-based Big Data and AI Benchmark Suite
As architecture, system, data management, and machine learning communiti...
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Data Dwarfs: A Lens Towards Fully Understanding Big Data and AI Workloads
The complexity and diversity of big data and AI workloads make understan...
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Big Data Dwarfs: Towards Fully Understanding Big Data Analytics Workloads
Though the big data benchmark suites like BigDataBench and CloudSuite ha...
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A Deep Learning Approach for Expert Identification in Question Answering Communities
In this paper, we describe an effective convolutional neural network fra...
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Depth First Always On Routing Trace Algorithm
In this paper, we discussed current limitation in the electronic-design-...
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A Dwarf-based Scalable Big Data Benchmarking Methodology
Different from the traditional benchmarking methodology that creates a n...
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Machine Learning Based Fast Power Integrity Classifier
In this paper, we proposed a new machine learning based fast power integ...
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Timing Aware Dummy Metal Fill Methodology
In this paper, we analyzed parasitic coupling capacitance coming from du...
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Non Uniform On Chip Power Delivery Network Synthesis Methodology
In this paper, we proposed a non-uniform power delivery network (PDN) sy...
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Customized Routing Optimization Based on Gradient Boost Regressor Model
In this paper, we discussed limitation of current electronic-design-auto...
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Isolate First, Then Share: a New OS Architecture for Datacenter Computing
This paper presents the "isolate first, then share" OS model in which th...
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