001451883 000__ 05771cam\a2200601\a\4500
001451883 001__ 1451883
001451883 003__ OCoLC
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001451883 019__ $$a1354993088
001451883 020__ $$a9783031218675$$q(electronic bk.)
001451883 020__ $$a3031218671$$q(electronic bk.)
001451883 020__ $$z9783031218668
001451883 020__ $$z3031218663
001451883 0247_ $$a10.1007/978-3-031-21867-5$$2doi
001451883 035__ $$aSP(OCoLC)1355216576
001451883 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX
001451883 049__ $$aISEA
001451883 050_4 $$aQA76.9.A73$$bA73 2022eb
001451883 08204 $$a004.2/2$$223/eng/20230104
001451883 1112_ $$aARCS (Conference)$$n(35th :$$d2022 :$$cHeilbronn, Germany)
001451883 24510 $$aArchitecture of computing systems :$$b35th International Conference, ARCS 2022, Heilbronn, Germany, September 13-15, 2022, Proceedings /$$cMartin Schulz, Carsten Trinitis, Nikela Papadopoulou, Thilo Pionteck (eds.).
001451883 2463_ $$aARCS 2022
001451883 260__ $$aCham :$$bSpringer,$$c2022.
001451883 300__ $$a1 online resource (293 p.).
001451883 4901_ $$aLecture notes in computer science ;$$v13642
001451883 500__ $$a4.3 Communication Between Processes
001451883 500__ $$aIncludes author index.
001451883 5050_ $$aIntro -- Preface -- Organization -- Keynote Talks -- SpMV: An Embarrassing Kernel for Modern Compute Devices -- Low-level Fun with Parallel Runtime Systems -- Contents -- Energy Efficiency -- Energy Efficient Frequency Scaling on GPUs in Heterogeneous HPC Systems -- 1 Motivation, Problem Statement and Key Contributions -- 1.1 Motivation -- 1.2 Problem Statement and Key Contributions -- 2 Related Work and Background -- 2.1 Performance and Energy Measurement Tools -- 2.2 Benchmarks -- 2.3 Energy Efficiency on Graphics Processing Units -- 3 Methodology -- 4 Results
001451883 5058_ $$a4.1 Minimum Interval Length Between Measurements -- 4.2 Frequency Scaling -- 4.3 Frequency vs. Total Energy Consumption -- 5 Summary, Future Research and Conclusion -- References -- Dual-IS: Instruction Set Modality for Efficient Instruction Level Parallelism -- 1 Introduction -- 2 Related Work -- 3 Transport Triggered Architectures -- 4 Dual-IS Processor -- 4.1 Instruction Translation -- 4.2 Micro-operation Sequencing -- 4.3 Control and Data Hazards -- 4.4 Mode Switching -- 5 Evaluation -- 5.1 Evaluated Designs -- 5.2 Synthesis Results -- 5.3 Performance -- 5.4 Energy Efficiency
001451883 5058_ $$a5.5 Discussion -- 6 Conclusions -- References -- Pasithea-1: An Energy-Efficient Self-contained CGRA with RISC-Like ISA -- 1 Introduction -- 1.1 Reconfigurable Computing -- 1.2 Related Work -- 1.3 This Work -- 2 Instruction Set Architecture -- 2.1 Fragment Instances -- 2.2 Local Interaction with Target Instruction Pointers (TIPs) -- 2.3 Global Interaction of Fragment Instances -- 2.4 What's the RISC? -- 3 Programming -- 3.1 Local Programming -- 3.2 Global Programming -- 4 Microarchitecture -- 4.1 Fragment Instance Management -- 4.2 Tiles and PEs: Fragment Instances on Fabric
001451883 5058_ $$a4.3 Dormant Fragment Instances -- 4.4 Memory Subsystem -- 5 Evaluation Methodology -- 6 Results -- 7 Discussion -- References -- Applied Machine Learning -- Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Motivation, Problem, and Solution Overview -- 3.1 Motivation: Technology Trends -- 3.2 Problem Definition -- 3.3 Solution Overview -- 4 Modeling and Optimization -- 4.1 Slowdown Estimation for a Given Job Set and Hardware Setup -- 4.2 Hardware Setup Optimization for a Given Job Set
001451883 5058_ $$a4.3 Job Sets Selection -- 5 Evaluation -- 5.1 Evaluation Setup -- 5.2 Experimental Results -- 6 Conclusion -- References -- FPGA-Based Dynamic Deep Learning Acceleration for Real-Time Video Analytics -- 1 Introduction -- 2 Overview of the Proposed System -- 2.1 Neural Network Architecture Search -- 2.2 Neural Network Model Compilation -- 2.3 Software and Hardware Run-Time Management -- 3 DNN Model Optimisation -- 3.1 Brief Introduction of OFA -- 3.2 Model Generation and Optimisation -- 4 System Hardware/Software Co-design -- 4.1 Hardware Architecture -- 4.2 Software Implementation
001451883 506__ $$aAccess limited to authorized users.
001451883 520__ $$aThis book constitutes the proceedings of the 35th International Conference on Architecture of Computing Systems, ARCS 2022, held virtually in July 2022. The 18 full papers in this volume were carefully reviewed and selected from 35 submissions. ARCS provides a platform covering newly emerging and cross-cutting topics, such as autonomous and ubiquitous systems, reconfigurable computing and acceleration, neural networks and artificial intelligence. The selected papers cover a variety of topics from the ARCS core domains, including energy efficiency, applied machine learning, hardware and software system security, reliable and fault-tolerant systems and organic computing.
001451883 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 4, 2023).
001451883 650_0 $$aComputer architecture$$vCongresses.
001451883 650_0 $$aComputer systems$$vCongresses.
001451883 655_0 $$aElectronic books.
001451883 7001_ $$aSchulz, Martin.
001451883 7001_ $$aTrinitis, Carsten.
001451883 7001_ $$aPapadopoulou, Nikela.
001451883 7001_ $$aPionteck, Thilo.
001451883 77608 $$iPrint version:$$aSchulz, Martin$$tArchitecture of Computing Systems$$dCham : Springer International Publishing AG,c2022$$z9783031218668
001451883 830_0 $$aLecture notes in computer science ;$$v13642.
001451883 852__ $$bebk
001451883 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-21867-5$$zOnline Access$$91397441.1
001451883 909CO $$ooai:library.usi.edu:1451883$$pGLOBAL_SET
001451883 980__ $$aBIB
001451883 980__ $$aEBOOK
001451883 982__ $$aEbook
001451883 983__ $$aOnline
001451883 994__ $$a92$$bISE