Mastering Concurrency: Advanced Programming Techniques for Efficiency

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Mastering Concurrency: Advanced Programming Techniques for Efficiency
Mastering Concurrency: Advanced Programming Techniques for Efficiency
1. Understanding Concurrency and Parallelism
The Difference Between Concurrency and Parallelism
Understanding Concurrency and Parallelism
  • Concurrency: Managing multiple tasks at once.
  • Parallelism: Executing multiple tasks simultaneously.
  • Time-slicing: Rapid switching between tasks.
FeatureDefinition
ConcurrencyManaging multiple tasks
ParallelismExecuting multiple tasks simultaneously
FeatureHardware Requirement
ConcurrencySingle processor
ParallelismMultiple processors/cores
FeatureGoal
ConcurrencyResponsiveness, handling multiple requests
ParallelismPerformance, reducing execution time
2. Threads and Processes: The Building Blocks of Concurrency
Working With Threads
Threads and Processes: The Building Blocks of Concurrency
  • Thread creation and management
  • Thread lifecycle management
  • Using thread pools.
FeatureMemory Space
ThreadShared
ProcessIndependent
FeatureResource Usage
ThreadLightweight
ProcessHeavyweight
FeatureCommunication
ThreadEfficient, shared memory
ProcessInter-process communication (IPC)
3. Synchronization Primitives: Avoiding Race Conditions
Mutexes, Semaphores, and Condition Variables
Synchronization Primitives: Avoiding Race Conditions
  • Mutexes: Exclusive access to resources.
  • Semaphores: Controlling concurrent access.
  • Condition Variables: Waiting for specific conditions.
PrimitiveMutex
PurposeExclusive access
MechanismLock/Unlock
PrimitiveSemaphore
PurposeControlled access
MechanismCounter
PrimitiveCondition Variable
PurposeWaiting for condition
MechanismWait/Signal
4. Concurrent Data Structures: Performance and Scalability
Optimizing data access
Concurrent Data Structures: Performance and Scalability
  • Concurrent hash maps
  • Concurrent queues
  • Lock-free algorithms
Data StructureConcurrent HashMap
Concurrency StrategyFine-grained locking
Use CaseHigh-concurrency key-value storage
Data StructureConcurrent Queue
Concurrency StrategyLock-free algorithms or fine-grained locking
Use CaseAsynchronous task processing
Data StructureCopy-on-Write Array
Concurrency StrategyCopy on write
Use CaseRead-heavy scenarios with infrequent updates
5. Asynchronous Programming: Non-Blocking Operations
Event Loops and Callbacks
Asynchronous Programming: Non-Blocking Operations
  • Event loops for handling events
  • Callbacks for asynchronous functions
  • Promises/async/await for cleaner code
FeatureBlocking
Synchronous ProgrammingYes
Asynchronous ProgrammingNo
FeatureResponsiveness
Synchronous ProgrammingLower
Asynchronous ProgrammingHigher
FeatureUse Case
Synchronous ProgrammingCPU-bound tasks
Asynchronous ProgrammingI/O-bound tasks
Conclusion
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