Physical Sciences and Mathematics Commons^™

Scalable Concurrent Hash Tables Via Relativistic Programming, Josh Triplett

Computer Science Faculty Publications and Presentations

Existing approaches to concurrent programming often fail to account for synchronization costs on modern shared-memory multipro- cessor architectures. A new approach to concurrent programming, known as relativistic programming, can reduce or in some cases eliminate synchronization overhead on such architectures. This approach avoids the costs of inter-processor communication and memory access by permitting processors to operate from a relativistic view of memory provided by their own caches, rather than from an absolute reference frame of memory as seen by all processors. This research shows how relativistic programming techniques can provide the perceived advantages of optimistic synchronization without the useless parallelism …

Compiling Ace For Distributed-Memory Machines, Jun Song

Dissertations and Theses

Distributed-memory machines offer a very high level of performance, flexibility and scalability. But the memory organization of this kind of machine determines that processes on different processors must communicate explicitly by sending and receiving messages. As a result, the programmer faces the enormously difficult task of detailed planning of algorithm-irrelevant, low-level communication issues. This level of programming resembles writing assembly programs for a sequential machine.

ACE is a message-passing language with abstract communication statements. It was defined by Dr. Jingke Li at Portland State University. The communication in ACE is still explicit, but it is abstracted to a higher level. …