Multi-threaded programming is difficult and error prone. It is easy to make a mistake in synchronization that produces a data race, yet it can be extremely hard to locate this mistake during debugging. This paper describes a new tool, called Eraser, for dynamically detecting data races in lock-based multi-threaded programs. Eraser uses binary rewriting techniques to monitor every shared memory reference and verify that consistent locking behavior is observed. We present several case studies, including undergraduate coursework and a multi-threaded Web search engine, that demonstrate the effectiveness of this approach.

Coscheduling has been shown to be a critical factor in achieving efficient parallel execution in timeshared environments [12,19,4]. However, the most common approach, gang scheduling, has limitations in scaling, can compromise good interactive response, and requires that communicating processes be identified in advance.We explore a technique called dynamic coscheduling (DCS) which produces emergent coscheduling of the processes constituting a parallel job. Experiments are performed in a workstation environment with high performance networks and autonomous timesharing schedulers for each CPU. The results demonstrate that DCS can achieve effective, robust coscheduling for a range of workloads and background loads. Empirical comparisons to implicit scheduling and uncoordinated scheduling are presented.Under spin-block synchronization, DCS reduces job response times by up to 20% over implicit scheduling while maintaining fairness; and under spinning synchronization, DCS reduces job response times by up to two decimal orders of magnitude over uncoordinated scheduling. The results suggest that DCS is a promising avenue for achieving coordinated parallel scheduling in an environment that coexists with autonomous node schedulers.

This thesis describes demand-based c oscheduling, a new approach t o s c heduling parallel computations on multiprogrammed multiprocessors. In demand-based coscheduling, rather than making the pessimistic assumption that all the processes constituting a parallel job must be simultaneously scheduled in order to achieve good performance, information about which processes are communicating is used in order to coschedule only these; the resulting scheme is well-suited to implementation on a w orkstation cluster because it is naturally decentralized. I present an analytical model and simulations of demand-based coscheduling, an implementation on a cluster of workstations connected by a high-speed network, and a set of experimental results. An analysis of the results shows that demand-based coscheduling successfully coschedules parallel processes in a timeshared workstation cluster, signi cantly reducing the response times of parallel computations. AbstractThis thesis describes demand-based c oscheduling, a new approach t o s c heduling parallel computations on multiprogrammed multiprocessors. In demand-based coscheduling, rather than making the pessimistic assumption that all the processes constituting a parallel job must be simultaneously scheduled in order to achieve good performance, information about which processes are communicating is used in order to coschedule only these; the resulting scheme is well-suited to implementation on a w orkstation cluster because it is naturally decentralized. I present an analytical model and simulations of demand-based coscheduling, an implementation on a cluster of workstations connected by a high-speed network, and a set of experimental results. An analysis of the results shows that demand-based coscheduling successfully coschedules parallel processes in a timeshared workstation cluster, signi cantly reducing the response times of parallel computations. Acknowledgments 1Sometimes when looking through a thesis I nd that it contains a very long acknowledgments section, which more often than not proves upon examination to be a very personal document. When the writer is a friend, I enjoy reading the acknowledgments, especially if my name is mentioned. When the writer is someone I know only professionally, m y reaction is typically embarassment tinged with distaste. I am reminded of a Peanuts cartoon I read when I wa s a c hild, in which Snoopy s a w a dog riding in a car with its head out the window and its tongue apping in the breeze. Snoopy thought that if he were in a car he would never behave in so undigni ed a manner; rather, he would sit up straight and wear a seat belt. It will be clear, then, that in order to maintain a digni ed posture and spare the reader embarassment, I should like to write a brief and formal acknowledgments section, but when I look back on the work that has occupied me for most of three years, I realize that that I am so indebted to colleagues, family, and friends, that to do so would be out of the question. Thus to the reader who does not kno...

Garbage collector performance in LISP systems on custom hardware has been substantially improved by the adoption of lifetime-based garbage collection techniques. To date, however, successful lifetime-based garbage collectors have required special-purpose hardware, or at least privileged access to data structures maintained by the virtual memory system. I present here a lifetime-based garbage collector requiring no special-purpose hardware or virtual memory system support, and discuss its performance.

Multi-threaded programming is difficult and error prone. It is easy to make a mistake in synchronization that produces a data race, yet it can be extremely hard to locate this mistake during debugging. This paper describes a new tool, called Eraser, for dynamically detecting data races in lock-based multi-threaded programs. Eraser uses binary rewriting techniques to monitor every shared memory reference and verify that consistent locking behavior is observed. We present several case studies, including undergraduate coursework and a multi-threaded Web search engine, that demonstrate the effectiveness of this approach.