410241 : High Performance Computing (SPPU)
410241 : High Performance Computing (SPPU)
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Credit 04
In-Sem (Paper): 30 Marks
End-Sem (Paper): 70 Marks
Credit 02 (partial from LP1 )
Term Work: 50 Marks
Practical: 50 Marks
Theory Syllabus at a Glance
Theory Syllabus at a Glance
High Performance Computing Syllabus
High Performance Computing Syllabus
Unit 1
Motivating Parallelism, Scope of Parallel Computing, Parallel Programming Platforms: Implicit Parallelism, Trends in Microprocessor and Architectures, Limitations of Memory, System Performance, Dichotomy of Parallel Computing Platforms, Physical Organization of Parallel Platforms, Communication Costs in Parallel Machines, Scalable design principles, Architectures: N-wide superscalar architectures, Multi-core architecture
Unit 2
Principles of Parallel Algorithm Design: Preliminaries, Decomposition Techniques, Characteristics of Tasks and Interactions, Mapping Techniques for Load Balancing, Methods for Containing Interaction Overheads, Parallel Algorithm Models, The Age of Parallel Processing, the Rise of GPU Computing, A Brief History of GPUs, Early GPU.
Unit 3
Operations- One-to-All Broadcast and All-to-One Reduction, All-to-All Broadcast and Reduction, All-Reduce and Prefix-Sum Operations, Scatter and Gather, All-to-All Personalized Communication, Circular Shift, Improving the Speed of Some Communication Operations.
Unit 4
Analytical Models: Sources of overhead in Parallel Programs, Performance Metrics for Parallel Systems, and The effect of Granularity on Performance, Scalability of Parallel Systems, Minimum execution time and minimum cost, optimal execution time. Dense Matrix Algorithms: MatrixVector Multiplication, Matrix-Matrix Multiplication.
Unit 5
Issues in Sorting on Parallel Computers, Bubble Sort and its Variants, Parallelizing Quick sort, All-Pairs Shortest Paths, Algorithm for sparse graph, Parallel Depth-First Search, Parallel BestFirst Search
Unit 6
CUDA Architecture, Using the CUDA Architecture, Applications of CUDA Introduction to CUDA C-Write and launch CUDA C kernels, Manage GPU memory, Manage communication and synchronization, Parallel programming in CUDA- C.
HPC Lab Assignments in LP 1
HPC Lab Assignments in LP 1
*Referring to the course outline and lap assignments, Course Teacher or Lab Instructor may frame the assignments/mini-project by understanding the prerequisites, technological aspects, utility and recent trends related to the respective courses.
So I have taken liberty to add QuickSort to the first Assignment
Parallel Sorting Algorithms For Bubble Sort and Merge Sort/Quick Sort, based on existing sequential algorithms, design and implement parallel algorithm utilizing all resources available.
Assignment Journal :
Submission date :20th Aug 2020
Marks: 05
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Vector and Matrix Operations Design parallel algorithm to 1. Add two large vectors 2. Multiply Vector and Matrix 3. Multiply two N × N arrays using nxn processors
Assignment Journal :
Submission date :
Marks: 05
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Parallel Search Algorithm- Design and implement parallel algorithm utilizing all resources available. for Binary Search for Sorted Array Depth-First Search ( tree or an un-directed graph )
Assignment Journal :
Binary Search Parallel Source Code
Binary Search Parallel Video
Submission date :
Marks: 05
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a) Implement Parallel Reduction using Min, Max, Sum and Average operations.
b) Write a CUDA program that, given an N-element vector,
The maximum element in the vector
The minimum element in the vector
The arithmetic mean of the vector
The standard deviation of the values in the vector
Test for input N and generate a randomized vector V of length N (N should be large). The program should generate output as the two computed maximum values as well as the time taken to find each value.
Assignment Journal :
Submission date :
Marks: 05
Resource Material
Resource Material
Link to Unit-2 PPT
On Roll List
On Roll List
Akash Balu Dongare
Snehal Bhagwat Shirsath
Rohit Modak
Shweta Mahesh Patvekar
Pranav Mahesh Khode
Soham Amit Merchant
Tanay Shrinivas Phadke
Rohit Rajendra Pandharbale
Omer KURKUTLU
Mlondi Jeffrey Mchunu
Pooja Prakash
Ajinkya Bhapkar
Mcebo Kevin Pateguanaa
Swarangi Kulkarni
Suyog Bhosale
Pradip Bagad
Sumit Pawar
Piyush Lohokare
Prashant sharma
Pranav Dhumal
VENU GOPAL JOSHI
Thawatchai Yango
Cluster .mp4MPIexec.mp4Page updated
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