摘要:
Encryption plays an important role in protecting data, especially data transferred on the Internet. However, encryption is computationally expensive and this leads to high energy costs. Parallel encryption solutions using more CPU/GPU cores can achieve high performance. If we consider energy efficiency to be cost effective using parallel encryption solutions at the same time, this problem can be alleviated effectively. Because many CPU/GPU cores and encryption are pervasive currently, saving energy cost by parallel encrypting has become an unavoidable problem. In this paper, we propose an energy-efficient parallel Advance Encryption Standard (AES) algorithm for CPU-GPU heterogeneous platforms. These platforms, such as the Green 500 computers, are popular in both high performance and general computing. Parallelizing AES, using both GPUs and CPUs, balances the workload between CPUs and GPUs based on their computing capacities. This approach also uses the Nvidia Management Library (N-VML) to adjust GPU frequencies, overlaps data transfers and computation, and fully utilizes GPU computing resources to reduce energy consumption as much as possible. Experiments conducted on a platform with one K20M GPU and two Xeon E5-2640 v2 CPUs show that this approach can reduce energy consumption by 74% compared to CPU-only parallel AES and 21% compared to GPU-only parallel AES on the same platform. Its energy efficiency is 4.66 MB/Joule on average higher than both CPU-only parallel AES (1.15 MB/Joule) and GPU-only parallel AES (3.65 MB/Joule). As an energy-efficient parallel AES solution, it can be used to encrypt data on heterogeneous platforms to save energy, especially for the computers with thousands of heterogeneous nodes.
作者机构:
Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University;Hunan Provincial Key Laboratory of Fine Ceramics and Powder Materials, School of Materials and Environmental Engineering, Hunan University of Humanities,Science and Technology;Department of Pharmaceutical Engineering, School of Chemical Engineering, Xiangtan University
会议名称:
2019中国化学会第十五届全国计算(机)化学学术会议
会议时间:
2019-11-14
会议地点:
中国上海
会议论文集名称:
2019中国化学会第十五届全国计算(机)化学学术会议论文集
关键词:
Source apportionment;PM10;PAHs;GC-MS;SCTDSR
摘要:
In the study, a new method based on the second-order calibration of three-way fingerprints of PAHs(SCTFP) was developed for the source apportionment of urban PM10 for the first time. First, simulated three-way data arrays of GC-MS were used to verify the feasibility of SCTFP. Then, PM10 and pollution source samples were collected during July and August, 2018 in Loudi City, China. After resolving the problems of GC-MS including baseline drift, retention-time shift and unexpected peaks overlapping, chromatographic and mass spectral profiles and concentrations of PAHs were accurately obtained by the second-order calibration of GC-MS data of samples. Last, a contribution matrix of the source to the receptor was estimated according to the obtained concentrations of PAHs. The proposed method was employed to apportion the source contributions to PM10 at five locations and reasonable results were obtained, thus presenting a promising tool for source apportionment of complex ambient particulate matter.
摘要:
This paper establishes evaluation indicators of the real estate marketing planning course teaching reform, uses relevant models of extension matter element theory to construct multidimensional extension matter element model of the real estate marketing planning course teaching reform evaluation, and uses cases to carry out empirical analysis. Empirical evidence shows that real estate marketing planning course teaching reform indicators are in line with the current direction of real estate marketing pluming courses teaching reform. The extension matter element evaluation method can evaluate complex, intersecting and uncertain real estate marketing planning course teaching reform indicators effectively, comprehensively and objectively, which is an effective evaluation method.