Introduction to parallel Programming in Open MP
87 videos • 44,482 views • by IIT Delhi July 2018
1
Introduction to Parallel Programming
Introduction to Parallel Programming in OpenMP
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2
Parallel Architectures and Programming Models
Introduction to Parallel Programming in OpenMP
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Pipelining
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Superpipelining and VLIW
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Memory Latency
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Cache and Temporal Locality
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Cache, Memory bandwidth and Spatial Locality
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Intuition for Shared and Distributed Memory architectures
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Shared and Distributed Memory architectures
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Interconnection networks in Distributed Memory architectures
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OpenMP: A parallel Hello World Program
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Program with Single thread
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Program Memory with Multiple threads and Multi-tasking
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Context Switching
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OpenMP: Basic thread functions
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OpenMP: About OpenMP
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Shared Memory Consistency Models and the Sequential Consistency Model
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Race Conditions
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OpenMP: Scoping variables and some race conditions
Introduction to Parallel Programming in OpenMP
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OpenMP: thread private variables and more constructs
Introduction to Parallel Programming in OpenMP
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Computing sum: first attempt at parallelization
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Manual distribution of work and critical sections
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Distributing for loops and reduction
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24
Vector-Vector operations (Dot product)
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Matrix-Vector operations (Matrix-Vector Multiply)
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Matrix-Matrix operations (Matrix-Matrix Multiply)
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Introduction to tasks
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Task queues and task execution
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Accessing variables in tasks
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Completion of tasks and scoping variables in tasks
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Recursive task spawning and pitfalls
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Understanding LU Factorization
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Parallel LU Factorization
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34
Locks
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Advanced Task handling
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Matrix Multiplication using tasks
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37
The OpenMP Shared Memory Consistency Model
Introduction to Parallel Programming in OpenMP
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38
Introduction to Parallel Programming
IIT Delhi July 2018
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39
OpenMP and MPI Course intro
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40
Parallel Architectures and Programming Models
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41
Application distributed histogram updation
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42
Applications deep learning
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43
Applications finite element method
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44
Discussion on MPI collectives design
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45
Introduction to MPI and basic calls
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46
MPI calls for broadcasting data
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MPI calls to send and receive data
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48
MPI collectives and MPI broadcast
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49
MPI gathering and scattering collectives
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50
MPI non blocking calls
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MPI reduction and alltoall collectives
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52
Alltoall on the Hypercube
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An improved algorithm for Alltoall on the Hypercube using E cube routing
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54
Broadcast and Reduce with recursive doubling
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55
Characteriziation of interconnects
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56
d dimensional torus
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Discussion of message sizes in analysis
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58
Hockney model
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59
Hypercube
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60
Linear arrays 2D mesh and torus
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61
Lower bounds
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62
Pipeline based algorithm for Allreduce
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63
Pipeline based algorithm for Broadcast
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64
Reduce scatter and All gather with recursive doubling
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Reduce scatter and Allreduce on the Hypercube
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66
Revisiting Reduce scatter on 2D mesh
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67
Scatter and Gather with recursive doubling
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68
Trees and cliques
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69
Introduction to parallel graph algorithms
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70
Prims Algorithm
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Performance considerations
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OpenMP based shared memory parallelization for MST
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MPI based distributed memory parallelization for MST
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Distributed memory settings and data distribution
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Distributed BFS algorithm
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Breadth First Search BFS using matrix algebra
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BFS Shared memory parallelization using OpenMP
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Sequential Algorithm Adaptation from Prims
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Parallelization Strategy for Prims algorithm
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80
Dry run with the parallel strategy
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81
Johnsons algorithm with 1D data distribution
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82
Speedup analysis on a grid graph
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83
Floyds algorithm for all pair shortest paths
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Floyds algorithm with 2D data distribution
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Adaptation to transitive closures
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86
Parallelization strategy for connected components
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87
Analysis for parallel connected components
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