Hasty Briefsbeta

Multi-Core by Default

9 hours ago
  • #multi-core-programming
  • #parallel-computing
  • #performance-optimization
  • Multi-core programming should be the default approach, not a special case, to leverage modern hardware capabilities.
  • Traditional single-core programming is complex, and adding multi-core programming on top increases complexity significantly.
  • Modern CPUs have multiple cores (8, 16, 32, 64), and ignoring multi-core programming leaves significant performance untapped.
  • The author initially avoided multi-core programming due to perceived complexity but later recognized its necessity for performance.
  • Multi-core programming introduces challenges like synchronization, debugging, and control flow scattering across threads.
  • A 'parallel for' loop is a common technique to distribute work across cores, but it has flaws like overhead and complexity.
  • Job systems can mitigate some overhead but still introduce complexity in setup, debugging, and maintenance.
  • GPU shader programming is multi-core by default, offering high performance with minimal programmer overhead, unlike CPU programming.
  • The author proposes a 'multi-core by default' approach, where code is written assuming multiple cores, with narrow (single-core) sections as needed.
  • This approach simplifies debugging, maintains full call stacks, and avoids the complexity of traditional job systems.
  • Key concepts include thread-local group data (LaneIdx, LaneCount, LaneSync), uniformly distributing work (LaneRange), and broadcasting data across lanes (LaneSyncU64).
  • The summation example demonstrates how to distribute work, combine results, and handle inputs/outputs in a multi-core context.
  • Non-uniform work distributions can be managed with dynamic task assignment or algorithm redesign (e.g., radix sort instead of comparison sort).
  • Multi-core by default is a strict superset of single-core programming, as it can parameterize down to single-core execution.
  • This approach is particularly useful for game engines, where heterogeneous timelines (e.g., rendering, input) require careful synchronization.
  • The author acknowledges that not all problems fit this model but argues it simplifies many multi-core scenarios.