CppCon 2026

Applications that present rapidly changing market data to human users face a practical challenge: updates may arrive thousands of times per second, but humans only benefit from periodic refreshes. Efficiently coalescing and scheduling that work without overwhelming CPU resources becomes a concurrency problem rather than simply a rendering problem.

This talk demonstrates how modern C++ atomics can be used to build a lock-free timer scheduler optimized for extremely high update rates. The scheduler follows a single-producer, multiple-consumer design in which work items represent recurring tasks that must execute periodically. Consumers process scheduled work and re-schedule it for future execution without relying on traditional locks or centralized coordination.

The most unusual aspect of the design is its “reverse work stealing” behavior: consumers can proactively give away work to other consumers and become idle themselves. Rather than distributing work evenly across all threads, the scheduler attempts to pack work onto as few cores as possible, reducing idle spinning, lowering CPU utilization, and improving cache locality. Because tasks may have highly variable execution times, the scheduler must also prevent pathological cases where work is endlessly redistributed between consumers.

Attendees will learn how atomics, lock-free forward lists, and memory ordering can be combined to implement high-throughput schedulers with predictable latency characteristics. The talk also discusses practical tradeoffs, implementation challenges, and performance measurements from production-inspired workloads, including producer throughput of approximately 50 million scheduled tasks per second and consumer processing throughput approaching 700 million tasks per second, while keeping migrated work items below 1% in typical workloads.