Proceedings of the 17th ACM International Conference on Computing Frontiers最新文献_第4页

Outlier detection based on sparse coding and neighbor entropy in high-dimensional space 基于稀疏编码和邻居熵的高维空间离群点检测

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-05-11 DOI: 10.1145/3387902.3392612

Ping Gu, Meng Chow, S. Shao

引用次数: 2

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-05-11 DOI: 10.1145/3387902.3394035

Xianglin Wei, Jianwei Liu, Junwei Wang, Yangang Wang, Jianhua Fan

{"title":"Similarity-aware popularity-based caching in wireless edge computing","authors":"Xianglin Wei, Jianwei Liu, Junwei Wang, Yangang Wang, Jianhua Fan","doi":"10.1145/3387902.3394035","DOIUrl":"https://doi.org/10.1145/3387902.3394035","url":null,"abstract":"Mobile edge computing (MEC) can greatly reduce the latency experienced by mobile devices and their energy consumption through bringing data processing, computing, and caching services closer to the source of data generation. However, existing edge caching mechanisms usually focus on predicting the popularity of contents or data chunks based on their request history. This will lead to a slow start problem for the newly arrived contents and fail to fulfill MEC's context-aware requirements. Moreover, the dynamic nature of contents as well as mobile devices has not been fully studied. Both of them hinder the further promotion and application of MEC caching. In this backdrop, this paper aims to tackle the caching problem in wireless edge caching scenarios, and a new dynamic caching architecture is proposed. The mobility of users and the dynamics nature of contents are considered comprehensively in our caching architecture rather than adopting a static assumption as that in many current efforts. Based on this framework, a Similarity-Aware Popularity-based Caching (SAPoC) algorithm is proposed which considers a content's freshness, short-term popularity, and the similarity between contents when making caching decisions. Extensive simulation experiments have been conducted to evaluate SAPoC's performance, and the results have shown that SAPoC outperforms several typical proposals in both cache hit ratio and energy consumption.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129710361","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: 2

Approximate trivial instructions 近似琐碎指令

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-05-11 DOI: 10.1145/3387902.3392623

Zayan Shaikh, E. Atoofian

{"title":"Approximate trivial instructions","authors":"Zayan Shaikh, E. Atoofian","doi":"10.1145/3387902.3392623","DOIUrl":"https://doi.org/10.1145/3387902.3392623","url":null,"abstract":"Approximate computing has the potential to improve performance and energy efficiency in high-performance processors. This work focuses on the impact of approximating conventionally non-trivial instructions to trivial instructions. Instructions which do not need to be processed due to the nature of their operands, such as division by 1 or addition with 0 are trivial instructions. By approximating instructions which results in an acceptable level of accuracy in programs' outputs, we can increase the number of trivial instructions and enhance power and performance of trivial bypassing. To approximate integer values, we mask the least significant bits (LSBs) of instructions' operands. The number of masked bits is under the control of programmers. To approximate floating-point values, we propose two different schemes. The first scheme sets a threshold and approximates the values that lie within the threshold region. A 32- or 64-bit comparator, depending on the operand size, is used for comparison between the operand and the threshold. Thus, instructions which would have used the expensive floating-point units are bypassed and only a comparator and a few gates are used instead. The second scheme reduces cost of approximation by replacing full-blown comparators with smaller ones and performing inexact comparisons between the operand and the threshold. Our evaluations using a diverse set of benchmarks reveal that precise comparison and trivial bypassing improve energy-delay by 21% and 13%, respectively while the inexact approximation improves energy-delay by 22%.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134560287","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: 2

Deffe

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-05-11 DOI: 10.1145/3387902.3392633

Frank Liu, Narasinga Rao Miniskar, Dwaipayan Chakraborty, J. Vetter

{"title":"Deffe","authors":"Frank Liu, Narasinga Rao Miniskar, Dwaipayan Chakraborty, J. Vetter","doi":"10.1145/3387902.3392633","DOIUrl":"https://doi.org/10.1145/3387902.3392633","url":null,"abstract":"As the computer architecture community moves toward the end of traditional device scaling, domain-specific architectures are becoming more pervasive. Given the number of diverse workloads and emerging heterogeneous architectures, exploration of this design space is a constrained optimization problem in a high-dimensional parameter space. In this respect, predicting workload performance both accurately and efficiently is a critical task for this exploration. In this paper, we present Deffe: a framework to estimate workload performance across varying architectural configurations. Deffe uses machine learning to improve the performance of this design space exploration. By casting the work of performance prediction itself as transfer learning tasks, the modelling component of Deffe can leverage the learned knowledge on one workload and \"transfer\" it to a new workload. Our extensive experimental results on a contemporary architecture toolchain (RISC-V and GEM5) and infrastructure show that the method can achieve superior testing accuracy with an effective reduction of 32-80× in terms of the amount of required training data. The overall run-time can be reduced from 400 hours to 5 hours when executed over 24 CPU cores. The infrastructure component of Deffe is based on scalable and easy-to-use open-source software components.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114346245","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

Approximating trigonometric functions for posits using the CORDIC method 用CORDIC方法逼近三角函数的位置

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-05-11 DOI: 10.1145/3387902.3392632

Jay P. Lim, Matan Shachnai, Santosh Nagarakatte

{"title":"Approximating trigonometric functions for posits using the CORDIC method","authors":"Jay P. Lim, Matan Shachnai, Santosh Nagarakatte","doi":"10.1145/3387902.3392632","DOIUrl":"https://doi.org/10.1145/3387902.3392632","url":null,"abstract":"Posit is a recently proposed representation for approximating real numbers using a finite number of bits. In contrast to the floating point (FP) representation, posit provides variable precision with a fixed number of total bits (i.e., tapered accuracy). Posit can represent a set of numbers with higher precision than FP and has garnered significant interest in various domains. The posit ecosystem currently does not have a native general-purpose math library. This paper presents our results in developing a math library for posits using the CORDIC method. CORDIC is an iterative algorithm to approximate trigonometric functions by rotating a vector with different angles in each iteration. This paper proposes two extensions to the CORDIC algorithm to account for tapered accuracy with posits that improves precision: (1) fast-forwarding of iterations to start the CORDIC algorithm at a later iteration and (2) the use of a wide accumulator (i.e., the quire data type) to minimize precision loss with accumulation. Our results show that a 32-bit posit implementation of trigonometric functions with our extensions is more accurate than a 32-bit FP implementation.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123004850","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: 9

Approximate approximation on a quantum annealer 量子退火炉的近似近似

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-04-20 DOI: 10.1145/3387902.3392635

I. Sax, Sebastian Feld, Sebastian Zieliński, Thomas Gabor, Claudia Linnhoff-Popien, W. Mauerer

{"title":"Approximate approximation on a quantum annealer","authors":"I. Sax, Sebastian Feld, Sebastian Zieliński, Thomas Gabor, Claudia Linnhoff-Popien, W. Mauerer","doi":"10.1145/3387902.3392635","DOIUrl":"https://doi.org/10.1145/3387902.3392635","url":null,"abstract":"Many problems of industrial interest are NP-complete, and quickly exhaust resources of computational devices with increasing input sizes. Quantum annealers (QA) are physical devices that aim at this class of problems by exploiting quantum mechanical properties of nature. However, they compete with efficient heuristics and probabilistic or randomised algorithms on classical machines that allow for finding approximate solutions to large NP-complete problems. While first implementations of QA have become commercially available, their practical benefits are far from fully explored. To the best of our knowledge, approximation techniques have not yet received substantial attention. In this paper, we explore how problems' approximate versions of varying degree can be systematically constructed for quantum annealer programs, and how this influences result quality or the handling of larger problem instances on given set of qubits. We illustrate various approximation techniques on both, simulations and real QA hardware, on different seminal problems, and interpret the results to contribute towards a better understanding of the real-world power and limitations of current-state and future quantum computing.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122487311","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: 26

Combining learning and optimization for transprecision computing 结合学习和优化的精度计算

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-02-24 DOI: 10.1145/3387902.3392615

Andrea Borghesi, Giuseppe Tagliavini, M. Lombardi, L. Benini, M. Milano

{"title":"Combining learning and optimization for transprecision computing","authors":"Andrea Borghesi, Giuseppe Tagliavini, M. Lombardi, L. Benini, M. Milano","doi":"10.1145/3387902.3392615","DOIUrl":"https://doi.org/10.1145/3387902.3392615","url":null,"abstract":"The growing demands of the worldwide IT infrastructure stress the need for reduced power consumption, which is addressed in so-called transprecision computing by improving energy efficiency at the expense of precision. For example, reducing the number of bits for some floating-point operations leads to higher efficiency, but also to a non-linear decrease of the computation accuracy. Depending on the application, small errors can be tolerated, thus allowing to fine-tune the precision of the computation. Finding the optimal precision for all variables in respect of an error bound is a complex task, which is tackled in the literature via heuristics. In this paper, we report on a first attempt to address the problem by combining a Mathematical Programming (MP) model and a Machine Learning (ML) model, following the Empirical Model Learning methodology. The ML model learns the relation between variables precision and the output error; this information is then embedded in the MP focused on minimizing the number of bits. An additional refinement phase is then added to improve the quality of the solution. The experimental results demonstrate an average speedup of 6.5% and a 3% increase in solution quality compared to the state-of-the-art. In addition, experiments on a hardware platform capable of mixed-precision arithmetic (PULPissimo) show the benefits of the proposed approach, with energy savings of around 40% compared to fixed-precision.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116481672","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: 7

Verified instruction-level energy consumption measurement for NVIDIA GPUs 经过验证的NVIDIA gpu指令级能耗测量

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2020-02-18 DOI: 10.1145/3387902.3392613

Yehia Arafa, Ammar Elwazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, S. Eidenbenz, N. Santhi

{"title":"Verified instruction-level energy consumption measurement for NVIDIA GPUs","authors":"Yehia Arafa, Ammar Elwazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, S. Eidenbenz, N. Santhi","doi":"10.1145/3387902.3392613","DOIUrl":"https://doi.org/10.1145/3387902.3392613","url":null,"abstract":"GPUs are prevalent in modern computing systems at all scales. They consume a significant fraction of the energy in these systems. However, vendors do not publish the actual cost of the power/energy overhead of their internal microarchitecture. In this paper, we accurately measure the energy consumption of various PTX instructions found in modern NVIDIA GPUs. We provide an exhaustive comparison of more than 40 instructions for four high-end NVIDIA GPUs from four different generations (Maxwell, Pascal, Volta, and Turing). Furthermore, we show the effect of the CUDA compiler optimizations on the energy consumption of each instruction. We use three different software techniques to read the GPU on-chip power sensors, which use NVIDIA's NVML API and provide an in-depth comparison between these techniques. Additionally, we verified the software measurement techniques against a custom-designed hardware power measurement. The results show that Volta GPUs have the best energy efficiency of all the other generations for the different categories of the instructions. This work should aid in understanding NVIDIA GPUs' microarchitecture. It should also make energy measurements of any GPU kernel both efficient and accurate.","PeriodicalId":155089,"journal":{"name":"Proceedings of the 17th ACM International Conference on Computing Frontiers","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126579587","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: 23

An evolutionary framework for automatic and guided discovery of algorithms 一个用于自动和引导算法发现的进化框架

Proceedings of the 17th ACM International Conference on Computing Frontiers Pub Date : 2019-04-05 DOI: 10.1145/3387902.3394033

Ruchira Sasanka, K. Krommydas

引用次数: 2