Parallel-Concurrent-and-Distributed-Programming-in-Java

Parallel, Concurrent, and Distributed Programming in Java | Coursera

Parallel Programming in Java

Week 1 : Task Parallelism

• Demonstrate task parallelism using Asynkc/Finish constructs
• Create task-parallel programs using Java's Fork/Join Framework
• Interpret Computation Graph abstraction for task-parallel programs
• Evaluate the Multiprocessor Scheduling problem using Computation Graphs
• Assess sequetional bottlenecks using Amdahl's Law

✅ Mini project 1 : Reciproncal-Array-Sum using the Java Fork/Join Framework

Week 2 : Functional Parallelism

• Demonstrate functional parallelism using the Future construct
• Create functional-parallel programs using Java's Fork/Join Framework
• Apply the princple of memoization to optimize functional parallelism
• Create functional-parallel programs using Java Streams
• Explain the concepts of data races and functional/structural determinism

✅ Mini project 2 : Analysing Student Statistics Using Java Parallel Streams

Week 3 : Loop Parallelism

• Create programs with loop-level parallelism using the Forall and Java Stream constructs
• Evaluate loop-level parallelism in a matrix-multiplication example
• Examine the barrier construct for parallel loops
• Evaluate parallel loops with barriers in an iterative-averaging example
• Apply the concept of iteration grouping/chunking to improve the performance of parallel loops

✅ Mini project 3 : Parallelizing Matrix-Matrix Multiply Using Loop Parallelism

Week 4 : Data flow Synchronization and Pipelining

• Create split-phase barriers using Java's Phaser construct
• Create point-to-point synchronization patterns using Java's Phaser construct
• Evaluate parallel loops with point-to-point synchronization in an iterative-averaging example
• Analyze pipeline parallelism using the principles of point-to-point synchronization
• Interpret data flow parallelism using the data-driven-task construct

✅ Mini project 4 : Using Phasers to Optimize Data-Parallel Applications

Concurrent Programming in Java

Week 1 : Threads and Locks

• Understand the role of Java threads in building concurrent programs
• Create concurrent programs using Java threads and the synchronized statement (structured locks)
• Create concurrent programs using Java threads and lock primitives in the java.util.concurrent library (unstructured locks)
• Analyze programs with threads and locks to identify liveness and related concurrency bugs
• Evaluate different approaches to solving the classical Dining Philosophers Problem

✅ Mini project 1 : Locking and Synchronization

Week 2 : Critical Sections and Isolation

• Create concurrent programs with critical sections to coordinate accesses to shared resources
• Create concurrent programs with object-based isolation to coordinate accesses to shared resources with more overlap than critical sections
• Evaluate different approaches to implementing the Concurrent Spanning Tree algorithm
• Create concurrent programs using Java's atomic variables
• Evaluate the impact of read vs. write operations on concurrent accesses to shared resources

✅ Mini project 2 : Global and Object-Based Isolation

Week 3 : Actors

• Understand the Actor model for building concurrent programs
• Create simple concurrent programs using the Actor model
• Analyze an Actor-based implementation of the Sieve of Eratosthenes program
• Create Actor-based implementations of the Producer-Consumer pattern
• Create Actor-based implementations of concurrent accesses on a bounded resource

✅ Mini project 3 : Sieve of Eratosthenes Using Actor Parallelism

Week 4 : Concurrent Data Structures

• Understand the principle of optimistic concurrency in concurrent algorithms
• Understand implementation of concurrent queues based on optimistic concurrency
• Understand linearizability as a correctness condition for concurrent data structures
• Create concurrent Java programs that use the java.util.concurrent.ConcurrentHashMap library
• Analyze a concurrent algorithm for computing a Minimum Spanning Tree of an undirected graph

✅ Mini project 4 : Parallelization of Boruvka's Minimum Spanning Tree Algorithm

Distributed Programming in Java

Week 1 : Distributed Map Reduce

• Explain the MapReduce paradigm for analyzing data represented as key-value pairs
• Apply the MapReduce paradigm to programs written using the Apache Hadoop framework
• Create Map Reduce programs using the Apache Spark framework
• Acknowledge the TF-IDF statistic used in data mining, and how it can be computed using the MapReduce paradigm
• Create an implementation of the PageRank algorithm using the Apache Spark framework

✅ Mini project 1 : Page Rank with Spark

Week 2 : Client-Server Programming

• Generate distributed client-server applications using sockets
• Demonstrate different approaches to serialization and deserialization of data structures for distributed programming
• Recall the use of remote method invocations as a higher-level primitive for distributed programming (compared to sockets)
• Evaluate the use of multicast sockets as a generalization of sockets
• Employ distributed publish-subscribe applications using the Apache Kafka framework

✅ Mini project 2 : Filer Server

Week 3 : Message Passing

• Create distributed applications using the Single Program Multiple Data (SPMD) model
• Create message-passing programs using point-to-point communication primitives in MPI
• Identify message ordering and deadlock properties of MPI programs
• Evaluate the advantages of non-blocking communication relative to standard blocking communication primitives
• Explain collective communication as a generalization of point-to-point communication

✅ Mini project 3 : Matrix Multiply in MPI

Week 4 : Combining Distribution and Multuthreading

• Distinguish processes and threads as basic building blocks of parallel, concurrent, and distributed Java programs
• Create multithreaded servers in Java using threads and processes
• Demonstrate how multithreading can be combined with message-passing programming models like MPI
• Analyze how the actor model can be used for distributed programming
• Assess how the reactive programming model can be used for distrubted programming

✅ Mini project 4 : Multi-Threaded File Server