LEADER 00449nas 2200157z- 450 001 9910718247103321 035 $a(CKB)4920000000044558 035 $a(EXLCZ)994920000000044558 100 $a20190616cuuuuuuuu -u- - 101 0 $aeng 200 00$aTiGenix N.V. Medtrack Company Profile 210 $cInforma Business Intelligence 906 $aJOURNAL 912 $a9910718247103321 996 $aTiGenix N.V. Medtrack Company Profile$93246911 997 $aUNINA LEADER 01224nam a22002771i 4500 001 991001397539707536 005 20031107155520.0 008 040407s1970 it a||||||||||||||||ita 035 $ab12764073-39ule_inst 035 $aARCHE-074370$9ExL 040 $aDip.to Scienze Storiche$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a759.5 245 02$aL'opera completa del Tintoretto /$cpresentazione di Carlo Bernari ; apparati critici e filologici di Pierluigi De Vecchi 260 $aMilano :$bRizzoli,$c[1970] 300 $a143 p. :$bill. ;$c32 cm 440 0$aClassici dell'arte 600 14$aTintoretto, Jacopo$xOPere$vCataloghi 700 1 $aBernari, Carlo$eauthor$4http://id.loc.gov/vocabulary/relators/aut$038384 700 1 $aDe Vecchi, Pierluigi 907 $a.b12764073$b02-04-14$c16-04-04 912 $a991001397539707536 945 $aLE009 LA Coll. 8/36$g1$i2009000173675$lle009$o-$pE0.00$q-$rn$so $t0$u2$v0$w2$x0$y.i13305347$z16-04-04 945 $aLE019 A12 AR F 41$g1$i2019000004473$lle019$op$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i15393070$z21-03-12 996 $aOpera completa del Tintoretto$91447627 997 $aUNISALENTO 998 $ale009$ale019$b16-04-04$cm$da $e-$fita$git $h2$i1 LEADER 02010oam 2200577 450 001 9910709646103321 005 20210413160153.0 035 $a(CKB)5470000002471776 035 $a(OCoLC)896811019 035 $a(OCoLC)995470000002471776 035 $a(EXLCZ)995470000002471776 100 $a20141123d1984 ba 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aWilderness mineral potential $eassessment of mineral-resource potential in U.S. Forest Service lands studied in 1964-1984 /$fedited by S.P. Marsh, S.J. Kropschot, and R.G. Dickinson ; prepared in cooperation with the U.S. Bureau of Mines 210 1$aWashington :$cUnited States Department of the Interior, Geological Survey,$d1984. 210 2$aWashington :$cUnited States Government Printing Office. 215 $a1 online resource (2 volumes) $cillustrations, maps 225 1 $aGeological Survey professional paper ;$v1300 300 $aTitle from title screen (viewed October 14, 2014). 320 $aIncludes bibliographical references and index. 517 $aWilderness mineral potential 606 $aMines and mineral resources$zUnited States 606 $aMines and mineral resources$2fast 607 $aUnited States$2fast 615 0$aMines and mineral resources 615 7$aMines and mineral resources. 700 $aMarsh$b Sherman P.$f1935-$01417242 702 $aKropschot$b S. J$g(Susan J.), 702 $aDickinson$b R. G$g(Robert G.), 712 02$aGeological Survey (U.S.), 712 02$aUnited States.$bBureau of Mines. 801 0$bCOP 801 1$bCOP 801 2$bOCLCO 801 2$bOCLCF 801 2$bCUS 801 2$bGPO 801 2$bOCL 801 2$bMERUC 801 2$bINT 801 2$bOCLCQ 801 2$bOCLCO 801 2$bGPO 906 $aBOOK 912 $a9910709646103321 996 $aWilderness mineral potential$93528464 997 $aUNINA LEADER 09371nam 2200493 450 001 996503564203316 005 20231110234138.0 010 $a3-031-23821-4 035 $a(MiAaPQ)EBC7161277 035 $a(Au-PeEL)EBL7161277 035 $a(CKB)25793102900041 035 $a(EXLCZ)9925793102900041 100 $a20230421d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aHigh performance computing $e9th Latin American conference, CARLA 2022, Porto Alegre, Brazil, September 26-30, 2022 : revised selected papers /$fedited by Philippe Navaux [and three others] 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (246 pages) 225 1 $aCommunications in Computer and Information Science ;$vv.1660 311 08$aPrint version: Navaux, Philippe High Performance Computing Cham : Springer International Publishing AG,c2022 9783031238208 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Contents -- A Comparative Evaluation of Parallel Programming Python Tools for Particle-in-Cell on Symmetric Multiprocessors -- 1 Introduction -- 2 Background -- 2.1 Particle-in-Cell -- 2.2 Python Parallel Programming -- 2.3 Related Work -- 3 Implementation -- 3.1 Profiling -- 3.2 Code Transformation -- 4 Experimental Results -- 4.1 Setup -- 4.2 Experiments -- 5 Discussion -- 6 Final Remarks -- References -- Accelerating GNN Training on CPU+Multi-FPGA Heterogeneous Platform -- 1 Introduction -- 2 Background -- 2.1 GNN Models -- 2.2 Mini-Batch GNN Training -- 2.3 Related Work -- 3 GNN Training on CPU+Multi-FPGA Platform -- 4 Optimizations -- 4.1 Graph Partitioning and Workload Balancing -- 4.2 Optimized GNN Kernels -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Hardware Parameter Selection and Resource Utilization -- 5.3 Performance Metrics -- 5.4 Comparison with Multi-GPU Platform -- 5.5 Scalability -- 5.6 Impact of Optimizations -- 6 Conclusion -- References -- Implementing a GPU-Portable Field Line Tracing Application with OpenMP Offload -- 1 Introduction -- 2 Background -- 2.1 Directive-Based Programming for Accelerators with OpenMP -- 2.2 Simulating Plasma Confinement in Stellarator Devices -- 2.3 Related Work -- 3 Directive-Based GPU Offloading Implementation -- 3.1 Breakdown of the Execution Flow -- 3.2 Data Management for Offloading -- 3.3 Parallelism Implementation -- 4 Results -- 4.1 Experimental Setup -- 4.2 Baseline Comparison: Single CPU Node Versus Single GPU -- 4.3 Multi-GPU Scalability -- 4.4 Economic Analysis -- 5 Conclusions -- References -- Quantitative Characterization of Scientific Computing Clusters -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Cluster Overhead and Coupling -- 3.2 Cluster Performance Profile -- 4 Performance Evaluation -- 4.1 Experimental Setup. 327 $a4.2 Threats to Validity -- 4.3 Results -- 4.4 Clusters Performance Profiles -- 5 Discussion -- 6 Conclusion -- References -- Towards Parameter-Based Profiling for MARE2DEM Performance Modeling -- 1 Introduction -- 2 Dataset and Application Background -- 2.1 CSEM Data -- 2.2 MARE2DEM -- 2.3 Refinement Groups -- 3 Methodology and Experimental Context -- 4 Results -- 4.1 Performance Characterization of the Microkernels -- 4.2 Iterations and Refinement Groups -- 5 Conclusion -- References -- Time-Power-Energy Balance of BLAS Kernels in Modern FPGAs -- 1 Introduction -- 2 FPGAs and NLA -- 2.1 BLAS -- 2.2 FPGAs -- 3 Evaluated Kernels -- 3.1 Vitis Libraries -- 3.2 Matrix-Matrix Multiplication (MMM) -- 4 Experimental Evaluation -- 4.1 Setup -- 4.2 Experimental Results and Discussion -- 5 Conclusions -- References -- Improving Boundary Layer Predictions Using Parametric Physics-Aware Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Boundary Layer Problem -- 3.2 Architecture Design -- 4 Experimental Results -- 4.1 First Setting: Reaction-Diffusion Problem -- 4.2 Second Setting: Advection-Diffusion Problem -- 5 Summary and Outlook -- References -- Towards Fire Identification Model in Satellite Images Using HPC Embedded Systems and AI -- 1 Introduction -- 2 Related Works -- 2.1 Satellite Imagery Multiscale Rapid Detection With Windowed Networks -- 2.2 Lapped Convolutional Neural Networks for Embedded Systems -- 3 Workflow -- 3.1 Dataset Elaboration -- 3.2 Algorithm Selection -- 4 Results -- 4.1 Artificial Learning -- 4.2 Evaluation Metrics -- 5 Conclusion -- 6 Future Work -- References -- A Machine Learning-Based Missing Data Imputation with FHIR Interoperability Approach in Sepsis Prediction -- 1 Introduction -- 2 State of the Art -- 2.1 Machine Learning on Clinical Features for Sepsis Prediction. 327 $a2.2 Interoperability of Healthcare Information Systems -- 3 Materials and Methods -- 3.1 Study Design -- 3.2 Dataset Early Prediction of Sepsis from Clinical Data -- 3.3 Processing and Transformation of Clinical Data to the FHIR Standard -- 3.4 Data Distribution - Hospitals A and B -- 3.5 Preprocessing of Data -- 3.6 Experiment Dataset -- 3.7 Creation of Train Test -- 3.8 Implementation of Classifiers -- 4 Experiments and Results -- 4.1 Experiment Results -- 5 Conclusions -- References -- Understanding the Energy Consumption of HPC Scale Artificial Intelligence -- 1 Introduction -- 2 Related Work -- 2.1 AI and Climate Change -- 2.2 Energy-Aware AI -- 2.3 AI Benchmarks -- 2.4 Energy Measurement Tools -- 2.5 Positioning of This Paper -- 3 Background -- 4 Benchmark Tracker -- 5 Results -- 5.1 Experimental Setting -- 5.2 Experimental Results -- 6 Conclusion and Future Work -- 6.1 Future Work -- References -- Using Big Data and Serverless Architecture to Follow the Emotional Response to the COVID-19 Pandemic in Mexico -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 General System Architecture -- 4 Experiments -- 5 Results -- 6 Conclusions -- References -- Multi-GPU 3-D Reverse Time Migration with Minimum I/O -- 1 Introduction -- 2 Reverse Time Migration -- 3 Computational Implementation and Optimizations -- 3.1 Classical Reverse Time Migration -- 3.2 Reverse Time Migration with Wavefield Reconstruction -- 3.3 Hybrid OpenACC/MPI Implementation -- 4 Numerical Experiments -- 5 Conclusions -- References -- ParslRNA-Seq: An Efficient and Scalable RNAseq Analysis Workflow for Studies of Differentiated Gene Expression -- 1 Introduction -- 2 Related Works -- 3 Background on Differential Gene Expression Analysis -- 4 ParslRNA-Seq: Workflow for DGE Analysis -- 4.1 Improvements in the Previous Implementation of the Workflow. 327 $a4.2 Multithreading and Multiprocessing -- 4.3 The Current Implementation of the ParslRNA-Seq Workflow -- 5 Methods and Infrastructure -- 5.1 Experiment Dataset -- 5.2 Experiment Setup -- 5.3 Computational Environment Setup -- 6 Experimental Results -- 6.1 Performance and Scalability Analyses -- 6.2 I/O Performance Results Using Darshan -- 6.3 Performance Results Using SSD -- 6.4 Biological Results of RNA-Seq Data -- 7 Conclusion -- References -- Refactoring an Electric-Market Simulation Software for Massively Parallel Computations -- 1 Introduction -- 2 The SimSEE and Previous Results -- 3 Proposal -- 3.1 Loading the Playrooms for Massively-Parallel Trajectories, naive -- 3.2 Improving the Playrooms Replication, base -- 3.3 Sharing References to Avoid Memory Allocations, RefCat -- 3.4 Enhancing the Access to Shared References in the Simulation, RefDicc -- 4 Experimental Evaluation -- 4.1 Test Cases -- 4.2 Runtime Environment -- 4.3 Experimental Results -- 5 Conclusion and Future Work -- References -- Nearly Quantum Computing by Simulation -- 1 Introduction -- 2 Quantum Computing Modelling -- 2.1 An Overview of Quantum Mechanics -- 2.2 Information Theory -- 2.3 Quantum Information Theory -- 3 Quantum Computing Parallelism and Simulation -- 3.1 Quantum Computing Simulators -- 3.2 Popular Open Source Quantum Computer Simulators -- 4 Discussion and Further Work -- References -- Functionality Testing in the Automation of Scientific Application Workflows in an HPC Environment -- 1 Introduction -- 2 Infrastructure Used -- 3 Tools Used -- 3.1 Slurm -- 3.2 Singularity -- 3.3 Snakemake -- 4 Design of the Processing Flow for Testing -- 5 Analysis of Possible Cases -- 5.1 Running Python Script -- 5.2 Running Python Script with SLURM and Singularity -- 5.3 Running a Singularity Container with Snakemake Using SLURM -- 5.4 Notes for Tables 2, 3 and 4. 327 $a6 Results of Executions -- 6.1 Case 1: -- 6.2 Case 2: -- 6.3 Case 3: -- 7 Discussion of Results and Conclusions -- 7.1 Testing Time -- 7.2 Duration of Tests -- 7.3 What Limitations There Were -- 7.4 Learning -- 7.5 Conclusions and Benefits -- References -- Author Index. 410 0$aCommunications in Computer and Information Science 606 $aHigh performance computing 606 $aHigh performance computing$vCongresses 615 0$aHigh performance computing. 615 0$aHigh performance computing 676 $a004.11 702 $aNavaux$b Philippe 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996503564203316 996 $aHigh Performance Computing$93000244 997 $aUNISA