Orca: a Portable User-Level Shared Object System

• Main Authors: Henri E. Bal, Raoul Bhoedjang, Rutger Hofman, Ceriel Jacobs, Koen Langendoen, Tim Rühl, M. Frans Kaashoek
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Published: 1996
• Subjects: General Terms; Languages; Design; Performance Additional Key Words and Phrases; distributed shared memory; parallel processing; Orca
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.31.9961

Orca is an object-based distributed shared memory system that is designed for writing portable and efficient parallel programs. Orca hides the communication substrate from the programmer by providing an abstract communication model based on shared objects. Mutual exclusion and condition synchronization are cleanly integrated in the model. Orca has been implemented using a layered system, consisting of a compiler, a runtime system, and a virtual machine (Panda). To implement shared objects efficiently on a distributed-memory machine, the Orca compiler generates regular expressions describing how shared objects are accessed. The runtime system uses this information together with runtime statistics to decide which objects to replicate and where to store nonreplicated objects. The Orca system has been implemented on a range of platforms (including Solaris, Amoeba, Parix, and the CM-5). Measurements of several benchmarks and applications across four platforms show that the new Orca system a.