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Full-Text Articles in Physical Sciences and Mathematics
Resizable, Scalable, Concurrent Hash Tables Via Relativistic Programming, Josh Triplett, Paul E. Mckenney, Jonathan Walpole
Resizable, Scalable, Concurrent Hash Tables Via Relativistic Programming, Josh Triplett, Paul E. Mckenney, Jonathan Walpole
Computer Science Faculty Publications and Presentations
Presentation focusing on software synchronization, thread locking, transactional memory, and relativistic programming. Hash table algorithms are presented with examples of relativistic list insertion and removal, and related data structures. Existing approaches are compared to new methodologies and future work with relativistic data structures.
A Relativistic Enhancement To Software Transactional Memory, Philip William Howard, Jonathan Walpole
A Relativistic Enhancement To Software Transactional Memory, Philip William Howard, Jonathan Walpole
Computer Science Faculty Publications and Presentations
Relativistic Programming is a technique that allows low overhead, linearly-scalable concurrent reads. It also allows joint access parallelism between readers and a writer. Unfortunately, it has so far been limited to a single writer so it does not scale on the write side. Software Transactional Memory (STM) is a technique that allows programs to take advantage of disjoint access parallelism on both the read-side and write-side. Unfortunately, STM systems have a higher overhead than many other synchronization mechanisms so although STM scales, STM starts from a lower baseline. We propose combining relativistic programming and software transactional memory in a way …
A Comparison Of Relativistic And Reader-Writer Locking Approaches To Shared Data Access, Philip William Howard, Josh Triplett, Jonathan Walpole
A Comparison Of Relativistic And Reader-Writer Locking Approaches To Shared Data Access, Philip William Howard, Josh Triplett, Jonathan Walpole
Computer Science Faculty Publications and Presentations
This paper explores the relationship between reader-writer locking and relativistic programming approaches to managing accesses to shared data. It demonstrates that by placing certain restrictions on writers, relativistic programming allows more concurrency than reader-writer locking while still providing the same isolation guarantees. Relativistic programming also allows for a straightforward model for reasoning about the correctness of programs that allow concurrent read-write accesses.
Haskell For The Cloud, Andrew P. Black
Haskell For The Cloud, Andrew P. Black
Computer Science Faculty Publications and Presentations
We present Cloud Haskell, a domain specific language for developing programs for a distributed-memory computing environment. Implemented as a shallow embedding in Haskell, it provides a message-passing communication model, inspired by Erlang, without introducing incompatibility with Haskell's established sharedmemory concurrency. A key contribution is a method for serializing function closures for transmission across the network. Cloud Haskell has been implemented; we present example code and some preliminary performance measurements.