Since world+dog uses multithreaded software, it’s nice to know that someone cares about what goes wrong with it.
A computer science group from Columbia University says it has a solution to “data races” in multithreaded programs, a common source of bugs and crashes. Its offering, called Peregrine, is the result of work at the Columbia Engineering School led by an assistant professor of computer science called Junfeng Yang.
In a paper called Efficient deterministic multithreading through schedule relaxation, co-authored with Heming Cui, Jingyue Wu, John Gallagher and Huayang Guo, Yang argues that most of a program's execution is race-free: “races tend to occur only in minor portions of an execution”, the paper states.
“Our main in developing Peregrine is that we can make threads deterministic in an efficient and stable way,” Yang says. “This prevents the random collisions that can occur in a non-deterministic system.”
The idea looks simple enough: the first time a program runs, Peregrine records a trace of the execution, computing an efficient plan for a group of threads. It can then “reuse the plan on subsequent groups [of threads] to avoid the cost of computing a new plan for each group,” Yang said.
Reusability of its execution plans, Yang says, is important to the long-term stability of the multithreading system. If the supervisor has to create new plans for any group of threads, it becomes more likely that some of its plans will have errors and create more collisions.
Avoiding crashes has a side-benefit, since crashes often leave machines vulnerable to attackers.
The research was published at the 23rd ACM Symposium on Operating Systems Principles, and the full paper can be found here. ®