Slowest CPU instruction runs for 62 seconds and costs 198 billion cycles

Searching for the Slowest Machine: How Researchers Are Stress-Testing CPU Limits

In the high-stakes world of processor design, the goal is usually simple: make instructions run as fast as possible. But what if you turned the objective around? What if instead of optimizing for speed, you aimed to find the absolute slowest possible execution time for a single low-level instruction?

This radical approach is the focus of a new experiment led by hardware researcher Christopher Domas, who is exploring the concept of CPU deoptimization. Rather than focusing on achieving peak performance, Domas is building a CPU deoptimization leaderboard that seeks to measure the maximum latency—the slowest possible time—for individual machine instructions.

This pursuit involves pushing processors to their architectural limits through deliberate stress testing. The goal isn’t just about speed; it’s about understanding the fundamental constraints of the hardware and how deeply embedded system operations affect instruction execution.

The results from this quest are astonishing. When competing against the conventional drive for efficiency, the team managed to achieve a score that measured 198 billion cycles—or over 62 seconds—for a single x86 instruction. This record demonstrates how much system-level friction and overhead can be introduced into the CPU pipeline.

To achieve these extreme latency measurements, Domas employed ingenious techniques to deliberately introduce bottlenecks. One method involved using their own custom tools to pinpoint high-latency areas within the internal PCIe fabric. By forcing the CPU to load state data through Memory-Mapped I/O (MMIO), they could observe how the system handles these slow communication channels.

Further escalating the challenge, the researchers went further by actively starving the system while operations were in flight. They overloaded the CPU’s PCIe root complex by forcing it to execute a series of frivolous read operations from other high-latency registers. This forced the critical instruction to queue behind unnecessary overhead, dramatically increasing its execution time.

The experiments also explored architectural features. By leveraging instructions like AMX available in Intel’s Sapphire Rapids, the team demonstrated that increasing data state size—from 512 bytes to 8 kilobytes—could cause an instruction to hang for over one trillion cycles, revealing potential ceilings on performance dictated by memory management.

The leaderboard, now live on GitHub, sets a new benchmark in low-level assembly experimentation. The rules are strict: only the execution of a single instruction is scored, and no hardware modifications are permitted during the test. This ensures that the ranking reflects not just the speed of the instruction itself, but what you do with it.

This type of research moves beyond conventional optimization by forcing engineers to look at the inherent relationship between software instructions and physical hardware architecture. It suggests that truly optimizing a CPU requires understanding the full spectrum of latency, even the moments when performance bottlenecks are intentionally exposed.