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Go_Concurrency: A repository showcasing Go's concurrency prowess through practical implementations using WaitGroup, channels, and atomic operations. Explore race condition mitigation and advanced patterns for effective concurrent programming.

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Go Concurrency

CPU Information Retrieval Commands on Windows

  • wmic cpu get NumberOfLogicalProcessors: Provides the count of logical processors (cores) available on the Windows system.
  • wmic cpu get NumberOfCores: Offers the count of physical cores available on the processor.

Definitions

  • Concurrency: The capability of an application to handle multiple tasks or processes simultaneously by interleaving their execution.
  • Parallelism: Simultaneous execution of multiple tasks genuinely running at the same time using multiple CPU cores.

Fork-Join in Go (Golang)

"Fork-join" in Go refers to dividing a task into smaller sub-tasks (forking), executing them independently, and then merging the results (joining) to produce the final output.

  • Fork: Breaking a task into smaller units for concurrent or parallel execution.
  • Join: Merging the results from individual tasks to form the final result.

Common Challenges in Concurrent Programming

  1. Race Conditions: Unpredictable behavior due to multiple threads accessing shared resources without synchronization.
  2. Deadlocks: Tasks waiting indefinitely for each other, halting progress.
  3. Livelocks: Continuous state changes without resolution, preventing progress.
  4. Resource Starvation: Inability to access necessary resources due to monopolization by other tasks.
  5. Synchronization Overhead: Introduction of synchronization mechanisms impacting performance and complexity.

Example Code

package main

import (
    "fmt"
    "sync"
)

func main() {
    var wg sync.WaitGroup
    wg.Wait()
    fmt.Println("Wait() executed immediately")
}

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Go_Concurrency: A repository showcasing Go's concurrency prowess through practical implementations using WaitGroup, channels, and atomic operations. Explore race condition mitigation and advanced patterns for effective concurrent programming.

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