Towards high-level execution primitives for and-parallelism: preliminary results

Most implementations of parallel logic programming rely on complex low-level machinery which is arguably difflcult to implement and modify. We explore an alternative approach aimed at taming that complexity by raising core parts of the implementation to the source language level for the particular case of and-parallelism. Therefore, we handle a signiflcant portion of the parallel implementation mechanism at the Prolog level with the help of a comparatively small number of concurrency-related primitives which take care of lower-level tasks such as locking, thread management, stack set management, etc. The approach does not eliminate altogether modiflcations to the abstract machine, but it does greatly simplify them and it also facilitates experimenting with different alternatives. We show how this approach allows implementing both restricted and unrestricted (i.e., non fork-join) parallelism. Preliminary experiments show that the amount of performance sacriflced is reasonable, although granularity control is required in some cases. Also, we observe that the availability of unrestricted parallelism contributes to better observed speedups.

Optimizing prolog for small devices: A case study

In this paper we present the design and implementation of a wearable application in Prolog. The application program is a "sound spatializer." Given an audio signal and real time data from a head-mounted compass, a signal is generated for stereo headphones that will appear to come from a position in space. We describe high-level and low-level optimizations and transformations that have been applied in order to fit this application on the wearable device. The end application operates comfortably in real-time on a wearable computer, and has a memory foot print that remains constant over time enabling it to run on continuous audio streams. Comparison with a version hand-written in C shows that the C version is no more than 20-40% faster; a small price to pay for a high level description.