Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems最新文献

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Bridge the Gap between Neural Networks and Neuromorphic Hardware with a Neural Network Compiler 用神经网络编译器弥合神经网络和神经形态硬件之间的差距

Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems Pub Date : 2017-11-15 DOI: 10.1145/3173162.3173205

Yu Ji, Youhui Zhang, Wenguang Chen, Yuan Xie

{"title":"Bridge the Gap between Neural Networks and Neuromorphic Hardware with a Neural Network Compiler","authors":"Yu Ji, Youhui Zhang, Wenguang Chen, Yuan Xie","doi":"10.1145/3173162.3173205","DOIUrl":"https://doi.org/10.1145/3173162.3173205","url":null,"abstract":"Different from developing neural networks (NNs) for general-purpose processors, the development for NN chips usually faces with some hardware-specific restrictions, such as limited precision of network signals and parameters, constrained computation scale, and limited types of non-linear functions. This paper proposes a general methodology to address the challenges. We decouple the NN applications from the target hardware by introducing a compiler that can transform an existing trained, unrestricted NN into an equivalent network that meets the given hardware's constraints. We propose multiple techniques to make the transformation adaptable to different kinds of NN chips, and reliable for restrict hardware constraints. We have built such a software tool that supports both spiking neural networks (SNNs) and traditional artificial neural networks (ANNs). We have demonstrated its effectiveness with a fabricated neuromorphic chip and a processing-in-memory (PIM) design. Tests show that the inference error caused by this solution is insignificant and the transformation time is much shorter than the retraining time. Also, we have studied the parameter-sensitivity evaluations to explore the tradeoffs between network error and resource utilization for different transformation strategies, which could provide insights for co-design optimization of neuromorphic hardware and software.","PeriodicalId":302876,"journal":{"name":"Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121428230","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: 53

Espresso: Brewing Java For More Non-Volatility with Non-volatile Memory 浓缩咖啡:用非易失性内存酿造更多的非易失性Java

Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems Pub Date : 2017-10-27 DOI: 10.1145/3173162.3173201

Mingyu Wu, Ziming Zhao, Haoyu Li, Heting Li, Haibo Chen, B. Zang, Haibing Guan

{"title":"Espresso: Brewing Java For More Non-Volatility with Non-volatile Memory","authors":"Mingyu Wu, Ziming Zhao, Haoyu Li, Heting Li, Haibo Chen, B. Zang, Haibing Guan","doi":"10.1145/3173162.3173201","DOIUrl":"https://doi.org/10.1145/3173162.3173201","url":null,"abstract":"Fast, byte-addressable non-volatile memory (NVM) embraces both near-DRAM latency and disk-like persistence, which has generated considerable interests to revolutionize system software stack and programming models. However, it is less understood how NVM can be combined with managed runtime like Java virtual machine (JVM) to ease persistence management. This paper proposes Espresso, a holistic extension to Java and its runtime, to enable Java programmers to exploit NVM for persistence management with high performance. Espresso first provides a general persistent heap design called Persistent Java Heap (PJH) to manage persistent data as normal Java objects. The heap is then strengthened with a recoverable mechanism to provide crash consistency for heap metadata. Espresso further provides a new abstraction called Persistent Java Object (PJO) to provide an easy-to-use but safe persistence programming model for programmers to persist application data. Evaluation confirms that Espresso significantly outperforms state-of-art NVM support for Java (i.e., JPA and PCJ) while being compatible to data structures in existing Java programs.","PeriodicalId":302876,"journal":{"name":"Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130594749","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: 52

Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems 程序设计语言和操作系统的架构支持第二十三届国际会议论文集

Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems Pub Date : 1900-01-01 DOI: 10.1145/3173162

引用次数: 1

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