Abstract TreadMarks: Shared Memory Computing on Networks of Workstations

TreadMarks supports parallel computing on networks of workstations by providing the application with a shared memory abstraction. Shared memory facilitates the transition from sequential to parallel programs. After identifying possible sources of parallelism in the code, most of the data structures can be retained without change, and only synchronization needs to be added to achieve a correct shared memory parallel program. Additional transformations may be necessary to optimize performance, but this can be done in an incremental fashion. We discuss the techniques used in TreadMarks to provide e cient shared memory, and our experience with two large applications, mixed integer programming and genetic linkage analysis.

Treadmarks: Shared memory computing on networks of workstations

TreadMarks supports parallel computing on networks of workstations by providing the application with a shared memory abstraction. Shared memory facilitates the transition from sequential to parallel programs. After identifying possible sources of parallelism in the code, most of the data structures can be retained without change, and only synchronization needs to be added to achieve a correct shared memory parallel program. Additional transformations may be necessary to optimize performance, but this can be done in an incremental fashion. We discuss the techniques used in TreadMarks to provide e cient shared memory, and our experience with two large applications, mixed integer programming and genetic linkage analysis.

Network Multicomputing Using Recoverable Distributed Shared Memory

A network multicomputer is a multiprocessor in which the processors are connected by general-purpose networking technology, in contrast to current distributedmemory multiprocessors where a dedicated special-purpose interconnect is used. The advent of high-speed general-purpose networks provides the impetus for a new look at the network multiprocessor model, by removing the bottleneck of current slow networks. However, major software issues remain unsolved. A convenient machine abstraction must be developed that hides from the application programmer low-level details such as message passing or machine failures. We use distributed shared memory as a programming abstraction, and rollback recovery through consistent checkpointing to provide fault tolerance. Measurements of our implementations of distributed shared memory and consistent checkpointing show that these abstractions can be implemented efficiently. 1 Introduction In most current distributed memory multicomputers [2] the process..