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The title should be evocative of the main point(s) of the activity. It needs to communicate the full context of the activity on its own as it will show up in places like search returns (e.g. Google) where people won't have any contextual clues. So it should convey the idea that this is a teaching activity, what the subject matter is and what the relevant pedagogical focus is. For example: Solar Radiation: Sample Socratic Questions
Name and institution of author(s) of the activity and any other appropriate attribution information. If the page is based on materials originally created elsewhere that should be noted with attribution given to the original authors and links provided to the original materials.
For example: This page authored by Jon Smith, Big State University, based on an original activity by Jane Smith, Smallville College.
Email addresses of the activity author(s) separated by commas. These will not be displayed in the activity page but are used for internal tracking.
This text should make it clear what the activity is. It should provide an overview of the things that students will do and the intended outcomes. The description should be concise and compelling: typically no more than 1-2 very brief paragraphs.
To prepare for this case study, students do background reading on landslides and rock avalanches and read the introductory portion of Hermanns and Strecker's 1999 article on rock avalanches in Argentina. In class, students receive data (assembled from figures in the article) on bedrock geology and physiography, as well as stereonets showing orientations of prominent joint sets, bedding, and foliations in the bedrock. Their task is to answer the question of why gigantic rock avalanches occur is some places but not others in this part of Argentina. The activity gives students practice in interpreting geologic maps, using stereonets, and peer teaching. Each student receives one of four possible data sets and must ultimately explain his/her analysis to others. The activity also connects structural geology to another geoscience discipline.
What concepts and content should students learn from this activity? Are there higher-order thinking skills (e.g. critical thinking, data analysis, synthesis of ideas, model development) that are developed by this activity? Are there other skills (writing, oral presentation, field techniques, equipment operation, etc.) that are developed by the activity.
This text should help faculty understand the types of teaching situations for which this activity is appropriate. Important types of context include educational level, class size, institution type, etc. Is it lab, lecture, or field exercise, or a longer project? How much time is needed for the activity. Is there special equipment that is necessary? Are there skills or concepts that students should have already mastered before encountering this activity? How is this activity situated in the course? How easy (or hard) would it be to adapt the activity for use in other settings?
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If you upload files as part of your activity remember to consider their final use in deciding on appropriate formats. Materials that other faculty are likely to modify should be provided in easily editable formats (plain text, Word files), whereas materials that will be likely only used verbatim are most convenient in formats that are universally readable (PDF format is often a good choice).
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e.g. 'Student Handout for Sauerkraut Assignment'
UnspecifiedJPEGGIFPNGSVGMicrosoft WordMicrosoft Word 2007 (.docx)PowerPointPowerPoint 2007 (.pptx)PowerPoint Slideshow (.ppsx)ExcelExcel 2007 (.xlsx)Excel 2007 macro-enabled (.xlsm)Acrobat (PDF)Rich Text FileText FileComma Separated ValuesFlash VideoQuicktime VideoFlash MP4 VideoMP4 VideoFlash AnimationMP3 AudioM4A AudioPhotoshopIllustratorKMLFileKMZ FileZip Archivegzip ArchiveStuffit ArchiveDisk Image FileHTML FileEncapsulated PostscriptPostscriptTIFFJar ArchiveJava Web StartWebM VideoOgg VideoStella RuntimeStella Model (v9 .stm)Stella Model (v10 .stmx)XML fileShockWave Component (SWC)Matlab .MAT FileMatlab FileMATLAB Live ScriptMathematica NotebookMathematica CDF fileCogsketch WorksheetWebVTTJupyter NotebookcalendarR scriptUnknown BinaryThe system will attempt to determine the correct file type based on the name of the file you've selected. Choosing the correct file type here will override that.
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This section should include notes and tips for instructors who might use the activity. Information such as common areas of confusion, things that need reinforcement, safety guidelines and other practical tips, and pointers for making the best use of the activity are appropriate.
This section should describe how the author determines whether or not students (either individually or collectively) are achieving the learning goals outlined for the activity. Other relevant assessment strategies may also be described in this section.
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The short description should be a distillation of the summary above. This description will be displayed in search returns. The optimal length for this description is on the order of 1-2 sentences.
Choose the relevant terms that help describe your module. Filling out this section will help other educators in knowing more about this module and determining if it will be a good fit for their curriculum (the characteristics will be located underneath the description). You may choose more than one term for each characteristic category if needed. If you would like a term to be added to a vocabulary, contact us.
Languages Supported Scheme Python C++ C Java Any Relevant Parallel Computing Concepts Data Parallelism Task Parallelism Message Passing Shared Memory Distributed Recommended Teaching Level Introductory Intermediate Advanced Any Possible Course Use Introduction to Computer Science Hardware Design Software Design Algorithm Design Parallel Computing Systems Programming Languages
Description about TCPP elements, their purpose, instructions.
Classes: Taxonomy Taxonomy Classes: Data vs. Control Parallelism Superscalar (ILP) SIMD/Vector (e.g., SSE, Cray) Pipelines - Data and control hazards Pipelines - OoO execution Pipelines - Single vs. Multicycle Streams (e.g., GPU) Dataflow MIMD Simultaneous Multi-Threading, Hyper-Threading Highly Multithreaded (e.g., MTA) Multicore Heterogeneous (e.g., Cell) Other Classes: Shared vs. Distributed Memory SMP - Buses NUMA/Shared Memory - Directory-based CC-NUMA NUMA/Shared Memory - CC-NUMA Message Passing - Bandwidth Message Passing - Circuit switching Message Passing - Diameter Message Passing - Latency Message Passing - Routing Message Passing - Packet Switching Message Passing - Topologies Other Memory Hierarchy Cache organization Atomicity Consistency Coherence False Sharing Impact on Software Floating Point Representation Range Precision Rounding Issues Error Propogation 754 Standard Performance Metrics Cycles per Instruction (CPI) Benchmark - Spec Mark Benchmark - Bandwidth Peak Performance MIPS/FLOPS Sustained Performance LinPack
Parallel Programming Paradigms: By The Target Machine Model SIMD Shared memory Distributed memory Client Server Hybrid Parallel Programming Paradigms: By The Control Statements Task/thread spawning SPMD Data Parallel Parallel Loop Parallel Programming Notations: Array Languages Microprocessor Vector Extensions Fortran 90/C++ Array Extensions Other Parallel Programming Notations: Shared Memory Notations Language Extensions Compiler Directives/Pragmas Libraries Other Parallel Programming Notations: SPMD Notations SPMD Notations Parallel Programming Notations: Functional/Logical Languages Functional/Logical Languages Semantics and Corrections Issues Tasks and Threads Synchronization Concurrency Defects Tools to Detect Concurrency Defects Performance Issues Computation Data Performance Monitoring Performance Metrics
Parallel and Distributed Models and Completxity: Costs of Computation Asymptotics Time Space Speedup Other Parallel and Distributed Models and Completxity: Cost Reduction Space Compression, etc. Other Parallel and Distributed Models and Completxity: Cost Tradeoffs Time vs. Space Power vs. Time Other Parallel and Distributed Models and Completxity: Scalability in Algorithms and Architectures Scalability in Algorithms and Architectures Parallel and Distributed Models and Completxity: Notations from Complexity Theory PRAM BSP/CILK Simulation/emulation P-Completeness #P=Completeness Cellular Automata Other Parallel and Distributed Models and Completxity: Notations From Scheduling Dependencies Task Graphs Work (Make) Span Other Algorithmic Paradigms Divide & Conquer Recursion Scan (Parallel Prefix) Reduction (Map-Reduce) Stencil-based Iteration "Oblivious" Algorithms Blocking Striping "Out-of-core" Algorithms Series-Parallel Composition Graph Embedding as an Algorithmic Tool Algorithmic Problems Communication: Broadcast Communication: Multicast Communication: Scatter/Gather Communication: Gossip Communication: Other Asynchrony Synchronization Sorting Selection Graph Algorithms: Sort Graph Algorithms: Path Selection Graph Algorithms: Other Convolutions Matrix Computations Termination Detection Leader Election/Symmetry Breaking Specialized Computations
High-level Themes Why and What is Parallel/Distributed Computing? Concurrency Topics Concurrency Non-Determinism Power Locality Current/Hot/Advanced Topics Cluster Cloud/Grid P2P Fault Tolerance Security in Distributed System Distributed Transactions Web Search Social Networking/Context Collaborative Computing Performance Modeling Web Services Pervasive Computing Mobile Computing
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