scholarly journals Evolution of the energy efficiency of LHCb’s real-time processing

2021 ◽  
Vol 251 ◽  
pp. 04009
Author(s):  
Roel Aaij ◽  
Daniel Hugo Cámpora Pérez ◽  
Tommaso Colombo ◽  
Conor Fitzpatrick ◽  
Vladimir Vava Gligorov ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Real Time ◽  
Lhcb Collaboration ◽  
Software Infrastructure ◽  
Real Time Processing ◽  
Time Processing ◽  
Lhcb Detector ◽  
Future Data ◽  
Time Part ◽  
The Impact

The upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4 TB/s in real time. Because LHCb’s physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this bandwidth challenge is equivalent to that of the ATLAS and CMS HL-LHC software read-out, but deliverable five years earlier. Over the past six years, the LHCb collaboration has undertaken a bottom-up rewrite of its software infrastructure, pattern recognition, and selection algorithms to make them better able to efficiently exploit modern highly parallel computing architectures. We review the impact of this reoptimization on the energy efficiency of the realtime processing software and hardware which will be used for the upgrade of the LHCb detector. We also review the impact of the decision to adopt a hybrid computing architecture consisting of GPUs and CPUs for the real-time part of LHCb’s future data processing. We discuss the implications of these results on how LHCb’s real-time power requirements may evolve in the future, particularly in the context of a planned second upgrade of the detector.

scholarly journals A Highly Efficient Heterogeneous Processor for SAR Imaging

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3409 ◽  
Author(s):  
Shiyu Wang ◽  
Shengbing Zhang ◽  
Xiaoping Huang ◽  
Jianfeng An ◽  
Libo Chang
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Real Time ◽  
Heterogeneous Computing ◽  
Floating Point ◽  
Phase Compensation ◽  
Real Time Processing ◽  
Time Processing ◽  
Array Architecture ◽  
Sar Imaging

The expansion and improvement of synthetic aperture radar (SAR) technology have greatly enhanced its practicality. SAR imaging requires real-time processing with limited power consumption for large input images. Designing a specific heterogeneous array processor is an effective approach to meet the power consumption constraints and real-time processing requirements of an application system. In this paper, taking a commonly used algorithm for SAR imaging—the chirp scaling algorithm (CSA)—as an example, the characteristics of each calculation stage in the SAR imaging process is analyzed, and the data flow model of SAR imaging is extracted. A heterogeneous array architecture for SAR imaging that effectively supports Fast Fourier Transformation/Inverse Fast Fourier Transform (FFT/IFFT) and phase compensation operations is proposed. First, a heterogeneous array architecture consisting of fixed-point PE units and floating-point FPE units, which are respectively proposed for the FFT/IFFT and phase compensation operations, increasing energy efficiency by 50% compared with the architecture using floating-point units. Second, data cross-placement and simultaneous access strategies are proposed to support the intra-block parallel processing of SAR block imaging, achieving up to 115.2 GOPS throughput. Third, a resource management strategy for heterogeneous computing arrays is designed, which supports the pipeline processing of FFT/IFFT and phase compensation operation, improving PE utilization by a factor of 1.82 and increasing energy efficiency by a factor of 1.5. Implemented in 65-nm technology, the experimental results show that the processor can achieve energy efficiency of up to 254 GOPS/W. The imaging fidelity and accuracy of the proposed processor were verified by evaluating the image quality of the actual scene.

GPU Acceleration of Algorithm to Design Directional Volumetric Display for Real-time Processing

2019 ◽  
pp. 989
Author(s):  
Daiki Matsumoto ◽  
Ryuji Hirayama ◽  
Naoto Hoshikawa ◽  
Hirotaka Nakayama ◽  
Tomoyoshi Shimobaba ◽  
...  
Keyword(s):  
Real Time ◽  
Gpu Acceleration ◽  
Real Time Processing ◽  
Time Processing ◽  
Volumetric Display

Putting up barriers

2017 ◽  
Author(s):  
David J. Lobina
Keyword(s):  
Knowledge Base ◽  
Real Time ◽  
Language Processing ◽  
Cognitive Domain ◽  
Linguistic Knowledge ◽  
Levels Of Explanation ◽  
Real Time Processing ◽  
Time Processing ◽  
Neural Underpinnings ◽  
Different Levels

The study of cognitive phenomena is best approached in an orderly manner. It must begin with an analysis of the function in intension at the heart of any cognitive domain (its knowledge base), then proceed to the manner in which such knowledge is put into use in real-time processing, concluding with a domain’s neural underpinnings, its development in ontogeny, etc. Such an approach to the study of cognition involves the adoption of different levels of explanation/description, as prescribed by David Marr and many others, each level requiring its own methodology and supplying its own data to be accounted for. The study of recursion in cognition is badly in need of a systematic and well-ordered approach, and this chapter lays out the blueprint to be followed in the book by focusing on a strict separation between how this notion applies in linguistic knowledge and how it manifests itself in language processing.

scholarly journals Limits on expectation-based processing: Use of grammatical aspect for co-reference in L2

2020 ◽  
pp. 1-25
Author(s):  
Theres Grüter ◽  
Hannah Rohde
Keyword(s):  
Real Time ◽  
Language Processing ◽  
Judgment Task ◽  
Linguistic Knowledge ◽  
Real Time Processing ◽  
Time Processing ◽  
Grammatical Aspect ◽  
Level Information ◽  
Native Speakers Of English ◽  
Reference Processing

Abstract This study examines the use of discourse-level information to create expectations about reference in real-time processing, testing whether patterns previously observed among native speakers of English generalize to nonnative speakers. Findings from a visual-world eye-tracking experiment show that native (L1; N = 53) but not nonnative (L2; N = 52) listeners’ proactive coreference expectations are modulated by grammatical aspect in transfer-of-possession events. Results from an offline judgment task show these L2 participants did not differ from L1 speakers in their interpretation of aspect marking on transfer-of-possession predicates in English, indicating it is not lack of linguistic knowledge but utilization of this knowledge in real-time processing that distinguishes the groups. English proficiency, although varying substantially within the L2 group, did not modulate L2 listeners’ use of grammatical aspect for reference processing. These findings contribute to the broader endeavor of delineating the role of prediction in human language processing in general, and in the processing of discourse-level information among L2 users in particular.

scholarly journals A Real Time Processing system for big data in astronomy: Applications to HERA

2021 ◽  
pp. 100489
Author(s):  
Paul La Plante ◽  
P.K.G. Williams ◽  
M. Kolopanis ◽  
J.S. Dillon ◽  
A.P. Beardsley ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Processing System ◽  
Real Time Processing ◽  
Time Processing

Real-Time Processing of Spaceborne SAR Data With Nonlinear Trajectory Based on Variable PRF

2021 ◽  
pp. 1-12
Author(s):  
Jianlai Chen ◽  
Junchao Zhang ◽  
Yanghao Jin ◽  
Hanwen Yu ◽  
Buge Liang ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Processing ◽  
Time Processing ◽  
Sar Data

scholarly journals A Set of Integral Grid-Coding Algebraic Operations Based on GeoSOT-3D

2021 ◽  
Vol 10 (7) ◽  
pp. 489
Author(s):  
Kaihua Hou ◽  
Chengqi Cheng ◽  
Bo Chen ◽  
Chi Zhang ◽  
Liesong He ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Data Retrieval ◽  
Geospatial Data ◽  
Algebraic Operation ◽  
Real Time Processing ◽  
C Language ◽  
Time Processing ◽  
Binary Operations ◽  
Set Operations

As the amount of collected spatial information (2D/3D) increases, the real-time processing of these massive data is among the urgent issues that need to be dealt with. Discretizing the physical earth into a digital gridded earth and assigning an integral computable code to each grid has become an effective way to accelerate real-time processing. Researchers have proposed optimization algorithms for spatial calculations in specific scenarios. However, a complete set of algorithms for real-time processing using grid coding is still lacking. To address this issue, a carefully designed, integral grid-coding algebraic operation framework for GeoSOT-3D (a multilayer latitude and longitude grid model) is proposed. By converting traditional floating-point calculations based on latitude and longitude into binary operations, the complexity of the algorithm is greatly reduced. We then present the detailed algorithms that were designed, including basic operations, vector operations, code conversion operations, spatial operations, metric operations, topological relation operations, and set operations. To verify the feasibility and efficiency of the above algorithms, we developed an experimental platform using C++ language (including major algorithms, and more algorithms may be expanded in the future). Then, we generated random data and conducted experiments. The experimental results show that the computing framework is feasible and can significantly improve the efficiency of spatial processing. The algebraic operation framework is expected to support large geospatial data retrieval and analysis, and experience a revival, on top of parallel and distributed computing, in an era of large geospatial data.

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