Lecture

FlowField Data Distribution

Related lectures (31)

Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.

Signal Representations

Covers matrix operations, Fourier transformations, Gaussian models, and signal representations using algebraic methods.

Generalization Error

Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.

Parallel Computing: Principles and OpenMP

Covers the principles of parallel computing and introduces OpenMP for creating concurrent code from serial code.

Principles of Parallel Computing: OpenMP

Explores the principles of parallel computing, focusing on OpenMP as a tool for creating concurrent code from serial code.

SmartDataLake: Distributed Analytics over Heterogeneous Data

Discusses challenges in scalable analytics over heterogeneous Big Data and introduces SmartDataLake for efficient handling of raw data.

Introduction to Multiprocessor Architecture

Introduces the fundamentals of multiprocessor architecture, covering post-Moore servers, sustainable datacenters, parallel programming, and GPU utilization.

Synchronization: Hardware Implementation

Explores hardware synchronization methods, including locks, barriers, and critical sections in parallel computing.

Synchronization

Covers the principles of synchronization in parallel computing, focusing on shared memory synchronization and different methods like locks and barriers.

Computer Science Evolution: Moore's Law to Multicores

Covers the evolution of computer science, from Moore's Law to multicores, research on parallelizing Lisp code, experiences at UC Berkeley and Microsoft Research, and insights on cloud computing and faculty management.

GPU Introduction: Performance and Programming

Explores the motivation and advantages of using GPUs for computation, focusing on their performance and programming through CUDA.

Synchronization: Locks and Barriers

Explores synchronization principles using locks and barriers, emphasizing efficient hardware-supported implementations and coordination mechanisms like OpenMP.

Asynchronous Programming with Futures

Explores asynchronous programming with futures, showcasing benefits, challenges, and efficient implementations.

Efficient GPU Join Optimization

Covers efficient GPU-accelerated join optimization for complex queries, focusing on improving optimization times and heuristic plan quality.

Scaling Trends: Transistors, Power Constraints, and Parallel Computing

Explores the evolution of transistors, power constraints, and the shift towards parallel computing in modern systems.

Conjugate Gradient Method: Solving Linear Systems

Covers the Conjugate Gradient method for solving linear systems without pre-conditioning, exploring parallel computing implementations and performance predictions.

Statistics: Exploratory Data Analysis

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

Concurrency with Futures

Explores futures as a structured approach to concurrency, simplifying parallel tasks and input-output operations.

MapReduce: Execution Models for Distributed Computing

Introduces the MapReduce programming model for distributed computing, focusing on its vision and under-the-hood mechanisms.

Transactional Memory: Two-phase Locking and Invisible Reads

Explores historical perspectives and mechanisms of transactional memory, emphasizing the importance and challenges of its implementation in modern computing systems.