Parallel science and engineering applications : the Charm++ approach / / edited by Laxmikant V. Kale, Abhinav Bhatele
| Parallel science and engineering applications : the Charm++ approach / / edited by Laxmikant V. Kale, Abhinav Bhatele |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton : , : CRC Press, , [2014] |
| Descrizione fisica | 1 online resource (302 p.) |
| Disciplina |
502.85/5133
502.855133 |
| Collana | Series in computational physics |
| Soggetto topico |
Engineering - Data processing
Science - Data processing Parallel processing (Electronic computers) Charm++ (Computer program language) |
| ISBN |
0-429-19414-5
1-4665-0412-9 |
| Classificazione | MAT000000MAT021000SCI055000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. The Charm++ programming model / Laxmikant V. Kale and Gengbin Zheng -- 2. Designing Charm++ programs / Laxmikant V. Kale -- 3. Tools for debugging and performance analysis / Filippo Gioachin, Chee Wai Lee, Jonathan Lifflander, Yanhua Sun and Laxmikant V. Kale -- 4. Scalable molecular dynamics with NAMD / James C. Phillips, Klaus Schulten, Abhinav Bhatele, Chao Mei, Yanhua Sun, Eric J. Bohm and Laxmikant V. Kale -- 5. OpenAtom : Ab initio molecular dynamics for petascale platforms / Glenn J. Martyna, Eric J. Bohm, Ramprasad Venkataraman, Laxmikant V. Kale and Abhinav Bhatele -- 6. N-body simulations with ChaNGa / Thomas R. Quinn, Pritish Jetley, Laxmikant V. Kale and Filippo Gioachin -- 7. Remote visualization of cosmological data using salsa / Orion Sky Lawlor and Thomas R. Quinn -- 8. Improving scalability of BRAMS : a regional weather forecast model / Eduardo R. Rodrigues, Celso L. Mendes and Jairo Panetta -- 9. Crack propagation analysis with automatic load balancing / Orion Sky Lawlor, M. Scot Breitenfeld, Philippe H. Geubelle and Gengbin Zheng -- 10. Contagion diffusion with EpiSimdemics / Keith R. Bisset, Ashwin M. Aji, Tariq Kamal, Jae-Seung Yeom, Madhav V. Marathe, Eric J. Bohm and Abhishek Gupta. |
| Altri titoli varianti | Charm++ approach |
| Record Nr. | UNINA-9910787334703321 |
| Boca Raton : , : CRC Press, , [2014] | ||
| Lo trovi qui: Univ. Federico II | ||
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Streamlining Your Research Laboratory with Python
| Streamlining Your Research Laboratory with Python |
| Autore | Russo Mark F |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (382 pages) |
| Disciplina | 502.85/5133 |
| Altri autori (Persone) | NeilWilliam |
| Soggetto topico |
Laboratories - Data processing
Python (Computer program language) |
| ISBN | 1-394-24990-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half Title Page -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1: Introduction -- 1.1 Python Implementations -- 1.2 Installing the Python Toolkit -- 1.3 Python 3 vs. Python 2 -- 1.4 Python Package Index -- 1.5 Programming Editors -- 1.6 Notebook Editors -- 1.7 Using the Jupyter Notebook Interface -- 1.8 JupyterLite -- 1.9 Things Change -- 1.10 Key Takeaways -- Chapter 2: Language Basics -- 2.1 Python Interactive Console -- 2.2 Data Types -- 2.3 Variables and Literals -- 2.4 Strings -- 2.4.1 Simple Strings -- 2.4.2 Multi-Line Strings -- 2.4.3 Escape Characters in a String -- 2.4.4 Raw Strings -- 2.4.5 Formatted Strings -- 2.4.6 Strings as Objects -- 2.4.7 Characters and Encodings -- 2.5 Expressions Using Operators -- 2.5.1 Arithmetic Operators -- 2.5.2 Assignment Operators -- 2.5.3 Comparison Operators -- 2.5.4 Boolean Operators -- 2.5.5 Chaining Comparisons -- 2.5.6 Comparing Floating-Point Numbers -- 2.6 Functions and How to Use Them -- 2.6.1 Invoking Functions -- 2.6.2 Built-in Functions -- 2.6.3 The math Module for Additional Mathematical Functions -- 2.6.4 The random Module for Pseudo-Random Number Generation -- 2.6.5 The time and datetime Modules for Handling Dates and Times -- 2.6.6 The sys Module for System Interactions -- 2.6.7 Scope and Namespace -- 2.7 Your First Python Program -- 2.8 Key Takeaways -- Chapter 3: Data Structures -- 3.1 Lists -- 3.1.1 Introducing Lists -- 3.1.2 Global Functions That Operate on Lists -- 3.1.3 Accessing List Elements -- 3.1.4 Slicing Lists -- 3.1.5 Lists Operators -- 3.1.6 Lists as Objects -- 3.2 Tuples -- 3.2.1 Introducing Tuples -- 3.3 Dictionaries -- 3.3.1 Introducing Dictionaries -- 3.3.2 Global Functions That Operate on Dictionaries -- 3.3.3 Accessing Dictionary Items -- 3.3.4 Dictionary Operators -- 3.3.5 Dictionaries as Objects -- 3.4 Sets -- 3.4.1 Introducing Sets.
3.4.2 Global Functions That Operate on Sets -- 3.4.3 Accessing Set Elements -- 3.4.4 Set Operators -- 3.4.5 Sets as Objects -- 3.5 Destructuring Assignment -- 3.6 Key Takeaways -- Chapter 4: Controlling the Flow of a Program -- 4.1 Conditional Execution -- 4.1.1 If-Statements -- 4.1.2 If-Else Statements -- 4.1.3 If-Elif-Else Statements -- 4.1.4 If-Statement Strategies -- 4.1.5 Truthy and Falsy Values -- 4.1.6 Conditional Expressions -- 4.2 Repeated Execution -- 4.2.1 While-Statements -- 4.2.2 For-Statements -- 4.2.3 For-Statements with Range -- 4.2.4 Break and Continue -- 4.2.5 Comprehensions -- 4.3 Key Takeaways -- Chapter 5: Custom Functions and Exceptions -- 5.1 Defining Custom Functions -- 5.2 Arguments and Parameters -- 5.3 Names and Scope -- 5.3.1 Local vs. Global -- 5.3.2 Built-in and Nonlocal Scope -- 5.4 Scope vs. Namespace -- 5.5 Organizing Your Code with Modules -- 5.6 Decorators -- 5.7 How Things Go Wrong -- 5.8 Python Exceptions -- 5.9 Handling Exceptions -- 5.10 Raising Your Own Exceptions -- 5.11 Key Takeaways -- Chapter 6: Regular Expressions -- 6.1 Matching Literal Text -- 6.2 Alternation -- 6.3 Defining and Matching Character Classes -- 6.4 Metaclasses -- 6.5 Pattern Sequences -- 6.6 Repeating Patterns with Quantifiers -- 6.7 Anchors -- 6.8 Capturing Groups -- 6.9 Regular Expressions in Python -- 6.10 Project - A Formula Mass Calculator -- 6.11 Key Takeaways -- Chapter 7: Working with Data -- 7.1 A File System Primer -- 7.2 Text Files -- 7.3 Reading and Writing Text Files -- 7.4 Working with Comma-Separated Values (CSV) Files -- 7.5 The csv Module -- 7.6 Reading and Writing Excel Spreadsheet -- 7.6.1 openpyxl Workbook Object -- 7.6.2 openpyxl Worksheet Object -- 7.6.3 openpyxl Cell Object -- 7.7 Project - Generate a Random Sample Layout in a Spreadsheet -- 7.8 Project - Forecast Monthly Sample Processing. 7.9 Managing the File System -- 7.9.1 The Path Object -- 7.9.2 Path Properties -- 7.9.3 Path Attributes -- 7.9.4 Operating On a Path -- 7.9.5 Combining Paths -- 7.9.6 The shutil Module for High-Level File Operations -- 7.10 Walking a File System Tree -- 7.11 Project - Find Duplicate Files -- 7.12 Working with Zip Files -- 7.12.1 ZipFile Object -- 7.12.2 zipfile Path Object -- 7.12.3 Creating Zip Archives -- 7.13 Working with Standard Data Formats -- 7.13.1 JSON - JavaScript Object Notation -- 7.13.2 json Python Module -- 7.13.3 XML - Extensible Markup Language -- 7.13.4 Python XML modules -- 7.13.5 Other Standard Data Formats -- 7.14 Key Takeaways -- Chapter 8: Web Resources -- 8.1 TCP/IP Networks - What You Need to Know -- 8.1.1 Internet Protocol -- 8.1.2 Transmission Control Protocol -- 8.1.3 Connections and Ports -- 8.1.4 Application Layer Protocols -- 8.1.5 IPv4 vs. IPv6 Addresses -- 8.1.6 Proxy Servers -- 8.2 Introduction to Hypertext Transfer Protocol -- 8.2.1 The Uniform Resource Locator -- 8.2.2 Anatomy of an HTTP Request -- 8.2.3 Anatomy of an HTTP Response -- 8.3 Web Services and the Python Requests Module -- 8.3.1 HTTP GET Requests and the Response Object -- 8.3.2 HTTP POST Requests -- 8.3.3 Binary Responses -- 8.3.4 Customizing the Request Object -- 8.3.5 Verifying Certificates and Encryption -- 8.3.6 Other requests Module Options -- 8.4 Project - Print Weather Forecast for a Location -- 8.4.1 National Weather Service API Web Service -- 8.4.2 Getting Forecast URL from Geolocation -- 8.4.3 Loading and Processing Forecast Data -- 8.4.4 Completed Program to Generate Temperature Forecast -- 8.5 Project - Scraping HTML Page Content -- 8.6 Key Takeaways -- Chapter 9: Data Analysis and Visualization -- 9.1 JupyterLab -- 9.2 Scientific Plotting with Matplotlib -- 9.2.1 The pyplot Submodule -- 9.2.2 The pyplot.plot() function. 9.2.3 Customizing a Plot -- 9.2.4 Multiple Curves on a Single Plot -- 9.2.5 Additional Plot Types -- 9.2.6 Multiple Axes on a Single Figure -- 9.2.7 Other Useful Functions -- 9.2.8 Project - Plotting Weather Forecast -- 9.2.9 Project - A Custom Microplate Heat Map -- 9.2.10 Other Scientific Plotting Libraries -- 9.3 NumPy - Numerical Python -- 9.3.1 Creating ndarray Objects -- 9.3.2 Working with ndarray Objects -- 9.3.3 Accessing and Updating ndarray Elements -- 9.3.4 Broadcasting -- 9.4 pandas DataFrame -- 9.4.1 Creating and Inspecting DataFrames -- 9.4.2 Filtering DataFrames -- 9.4.3 Project - A Screening Experiment -- 9.5 SciPy - A Library for Mathematics, Science, and Engineering -- 9.5.1 Descriptive Statistics with SciPy -- 9.5.2 Hypothesis Testing -- 9.5.3 Project - Running Hypothesis Tests on Two Samples -- 9.5.4 Project - Comparing Liquid Handler Syringe Performance -- 9.5.5 Linear Regression -- 9.5.6 Fitting Nonlinear Models to Data -- 9.5.7 Project - Four-Parameter Logistic Regression -- 9.6 Key Takeaways -- Chapter 10: Report Generation -- 10.1 BytesIO Object -- 10.2 Generating Reports in Microsoft Word -- 10.2.1 Document Object -- 10.2.2 Paragraph Object -- 10.2.3 Run Object -- 10.2.4 Picture and InlineShape Objects -- 10.2.5 Table Object -- 10.2.6 Project - Generate a Complete Word Report -- 10.3 Generating Microsoft PowerPoint Presentations -- 10.3.1 Presentation Object -- 10.3.2 Slide Objects -- 10.3.3 SlideShapes Object -- 10.3.4 Length Objects -- 10.3.5 Table Object -- 10.3.6 Project - Generate a PowerPoint Document with Figures and Tables -- 10.4 Generating PDF File Reports -- 10.4.1 ReportLab PDF Generation Process -- 10.4.2 Creating a Canvas Object -- 10.4.3 Setting Canvas Styles -- 10.4.4 Managing Text Blocks with PDFTextObjects -- 10.4.5 Canvas State Stack -- 10.4.6 Drawing Images -- 10.4.7 PLATYPUS for Page Layout. 10.4.8 Project - Generate a Complete PDF Report -- 10.5 Sending Email Programmatically -- 10.5.1 Simple Mail Transfer Protocol -- 10.5.2 SMTP Mail Server -- 10.5.3 Send a Simple Email Message -- 10.5.4 Sending Email Messages over a Secure Connection -- 10.5.5 Building an Email Message with Attachments -- 10.6 Serving Results with an HTTP Server -- 10.7 Key Takeaways -- Chapter 11: Control and Automation -- 11.1 Concurrency in Python -- 11.2 Asynchronous Execution -- 11.3 Concurrent Programs with AsyncIO -- 11.4 Asynchronous Instrument Control and Coordination -- 11.4.1 Project - Integrated Laboratory System Control and Coordination -- 11.5 Communicating over a Serial Port -- 11.5.1 Reading Barcodes from a Serial Port -- 11.5.2 Project - Scanning Sample Tasks into a Running Controller -- 11.6 Execute Remote Commands over HTTP -- 11.6.1 A Basic HTTP Server with aiohttp -- 11.6.2 Routing an HTTP Request to a Custom Python Function -- 11.7 Persistent Network Connections using a WebSocket -- 11.7.1 A User Interface for Asynchronous Networked Programs -- 11.7.2 WebSocketResponse and FileResponse Objects -- 11.7.3 Project - A Browser-Based WebSocket Message Broadcaster -- 11.7.4 Project - A Browser User Interface to Schedule Samples for Analysis -- 11.8 Responding to File System Changes -- 11.8.1 Watching a Directory for Changes with watchfiles -- 11.8.2 File System Monitoring Options -- 11.9 Executing Tasks on a Schedule -- 11.9.1 sched Module -- 11.9.2 Project - Taking and Sending Images on a Schedule -- 11.10 Key Takeaways -- Postface -- References -- Appendix A: ASCII American Standard Code for Information Interchange -- Index -- EULA. |
| Record Nr. | UNINA-9911030980203321 |
Russo Mark F
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Lo trovi qui: Univ. Federico II | ||
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