2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)最新文献_第10页

Peering Into the Anneal Process of a Quantum Annealer 探讨量子退火炉的退火过程

2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) Pub Date : 2019-08-07 DOI: 10.1109/PDCAT46702.2019.00043

Elijah Pelofske, Georg Hahn, H. Djidjev

{"title":"Peering Into the Anneal Process of a Quantum Annealer","authors":"Elijah Pelofske, Georg Hahn, H. Djidjev","doi":"10.1109/PDCAT46702.2019.00043","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00043","url":null,"abstract":"Commercial adiabatic quantum annealers have the potential to solve important NP-hard optimization problems efficiently. The newest generation of those machines additionally allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the annealing. In this work we use the aforementioned feature of the D-Wave 2000Q to attempt to monitor how the anneal solution evolves during the anneal process. This process we call slicing: at each time slice during the anneal, we are able to obtain an approximate distribution of anneal solutions. We use our technique to obtain a variety of insights into the D-Wave 2000Q. For example, we observe when individual bits flip during the anneal process and when they stabilize, which allows us to determine the freeze-out point for each qubit individually. We highlight our results using both random QUBO (quadratic unconstrained binary optimization) instances and, for better visualization, instances which we specifically optimize (using our own genetic algorithm) to exhibit a pronounced evolution of its solution during the anneal.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130368398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Attention-Based Supply-Demand Prediction for Autonomous Vehicles 基于注意力的自动驾驶汽车供需预测

2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) Pub Date : 2019-05-27 DOI: 10.1109/PDCAT46702.2019.00085

Zikai Zhang, Yidong Li, Hai-rong Dong, Yizhe You, Fengping Zhao

引用次数: 3

Succinct Representations in Collaborative Filtering: A Case Study using Wavelet Tree on 1,000 Cores 协同过滤中的简洁表示：在 1,000 个内核上使用小波树的案例研究

2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) Pub Date : 2019-03-12 DOI: 10.1109/PDCAT46702.2019.00083

Xiangjun Peng, Qingfeng Wang, Xu Sun, Chunye Gong, Yaohua Wang

{"title":"Succinct Representations in Collaborative Filtering: A Case Study using Wavelet Tree on 1,000 Cores","authors":"Xiangjun Peng, Qingfeng Wang, Xu Sun, Chunye Gong, Yaohua Wang","doi":"10.1109/PDCAT46702.2019.00083","DOIUrl":"https://doi.org/10.1109/PDCAT46702.2019.00083","url":null,"abstract":"User-Item (U-I) matrix has been used as the dominant data infrastructure of Collaborative Filtering (CF). To reduce space consumption in runtime and storage, caused by data sparsity and growing need to accommodate side information in CF design, one needs to go beyond the U-I Matrix. In this paper, we took a case study of Succinct Representations in Collaborative Filtering, rather than using a U-I Matrix. Our key insight is to introduce Succinct Data Structures as a new infrastructure of CF. Towards this, we implemented a User-based K-Nearest-Neighbor CF prototype via Wavelet Tree, by first designing a Accessible Compressed Documents (ACD) to compress U-I data in Wavelet Tree, which is efficient in both storage and runtime. Then, we showed that ACD can be applied to develop an efficient intersection algorithm without decompression, by taking advantage of ACD's characteristics. We evaluated our design on 1,000 cores of Tianhe-II supercomputer, with one of the largest public data set ml-20m. The results showed that our prototype could achieve 3.7 minutes on average to deliver the results.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128030581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

External Reviewers 审稿人

2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) Pub Date : 2018-06-01 DOI: 10.1109/SP.2006.15

M. Hewelt

引用次数: 0