- Intel Threading Building Blocks
- Foreword
- Note from the Lead Developer of Intel Threading Building Blocks
- Preface
- 1. Why Threading Building Blocks?
- 2. Thinking Parallel
- 3. Basic Algorithms
- 4. Advanced Algorithms
- 5. Containers
- 6. Scalable Memory Allocation
- 7. Mutual Exclusion
- 8. Timing
- 9. Task Scheduler
- When Task-Based Programming Is Inappropriate
- Much Better Than Raw Native Threads
- Initializing the Library Is Your Job
- Example Program for Fibonacci Numbers
- Task Scheduling Overview
- How Task Scheduling Works
- Recommended Task Recurrence Patterns
- Making Best Use of the Scheduler
- Task Scheduler Interfaces
- Task Scheduler Summary
- 10. Keys to Success
- 11. Examples
- The Aha! Factor
- A Few Other Key Points
- parallel_for Examples
- The Game of Life
- Parallel_reduce Examples
- CountStrings: Using concurrent_hash_map
- Quicksort: Visualizing Task Stealing
- A Better Matrix Multiply (Strassen)
- Advanced Task Programming
- Packet Processing Pipeline
- Memory Allocation
- Game Threading Example
- Physics Interaction and Update Code
- Open Dynamics Engine
- 12. History and Related Projects
- Index
- About the Author
- Colophon
- Copyright
As emphasized earlier in this chapter, the Threading Building Blocks containers are not likely to provide adequate performance when used with general C++ memory routines. A production-quality solution to memory allocation requires some custom memory-allocation functions that reflect your operating system and C++ compiler. You can make the replacement in one of the following ways:
Replace
malloc/freeand related memory routines (C programs).Replace global
newanddeleteoperators (C++ programs).
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