Deterministic multithreading (DMT) eliminates many pernicious software problems caused by nondeterminism. It works by constraining a program to repeat the same thread interleavings, or schedules, when given same input. Despite much recent research, it remains an open challenge to build both deterministic and efficient DMT systems for general programs on commodity hardware. To deterministically resolve a data race, a DMT system must enforce a deterministic schedule of shared memory accesses, or memschedule, which can incur prohibitive overhead. By using schedules consisting only of synchronization operations, or sync-schedule, this overhead can be avoided. However, a sync-schedule is deterministic only for race-free programs, but most programs have races.Our key insight is that races tend to occur only within minor portions of an execution, and a dominant majority of the execution is still race-free. Thus, we can resort to a mem-schedule only for the "racy" portions and enforce a sync-schedule otherwise, combining the efficiency of sync-schedules and the determinism of memschedules. We call these combined schedules hybrid schedules.Based on this insight, we have built PEREGRINE, an efficient deterministic multithreading system. When a program first runs on an input, PEREGRINE records an execution trace. It then relaxes this trace into a hybrid schedule and reuses the schedule on future compatible inputs efficiently and deterministically. PEREGRINE further improves efficiency with two new techniques: determinismpreserving slicing to generalize a schedule to more inputs while preserving determinism, and schedule-guided simplification to precisely analyze a program according to a specific schedule. Our evaluation on a diverse set of programs shows that PEREGRINE is deterministic and efficient, and can frequently reuse schedules for half of the evaluated programs.

Deployed multithreaded applications contain many races because these applications are difficult to write, test, and debug. Worse, the number of races in deployed applications may drastically increase due to the rise of multicore hardware and the immaturity of current race detectors. LOOM is a "live-workaround" system designed to quickly and safely bypass application races at runtime. LOOM provides a flexible and safe language for developers to write execution filters that explicitly synchronize code. It then uses an evacuation algorithm to safely install the filters to live applications to avoid races. It reduces its performance overhead using hybrid instrumentation that combines static and dynamic instrumentation. We evaluated LOOM on nine real races from a diverse set of six applications, including MySQL and Apache. Our results show that (1) LOOM can safely fix all evaluated races in a timely manner, thereby increasing application availability; (2) LOOM incurs little performance overhead; (3) LOOM scales well with the number of application threads; and (4) LOOM is easy to use.

Stable multithreading dramatically simplifies the interleaving behaviors of parallel programs, offering new hope for making parallel programming easier.

State machine replication (SMR) leverages distributed consensus protocols such as PAXOS to keep multiple replicas of a program consistent in face of replica failures or network partitions. This fault tolerance is enticing on implementing a principled SMR system that replicates general programs, especially server programs that demand high availability. Unfortunately, SMR assumes deterministic execution, but most server programs are multithreaded and thus nondeterministic. Moreover, existing SMR systems provide narrow state machine interfaces to suit specific programs, and it can be quite strenuous and error-prone to orchestrate a general program into these interfaces This paper presents CRANE, an SMR system that transparently replicates general server programs. CRANE achieves distributed consensus on the socket API, a common interface to almost all server programs. It leverages deterministic multithreading (specifically, our prior system PARROT) to make multithreaded replicas deterministic. It uses a new technique we call time bubbling to efficiently tackle a difficult challenge of nondeterministic network input timing. Evaluation on five widely used server programs (e.g., Apache, ClamAV, and MySQL) shows that CRANE is easy to use, has moderate overhead, and is robust. CRANE's source code is at github.com/columbia/crane.