Evaluation of hardware architectures for parallel execution of complex database operations

Abstract New database applications, primarily in the areas of engineering and knowledge-based systems, refer to complex objects (e.g. representation of a CAD workpiece or a VLSI chip) while performing their tasks. Retrieval, maintenance, and integrity checking of such complex objects consume substantial computing resources which were traditionally used by conventional database management systems in a sequential manner. Rigid performance goals dictated by interactive use and design environments imply new approaches to master the functionality of complex objects under satisfactory time restrictions. Because of the object granularity, the set orientation of the database interface, and the complicated algorithms for object handling, the exploitation of parallelism within such operations seems to be promising. Our main goal is the investigation and evaluation of different hardware architectures and their suitability to efficiently cope with workloads generated by database operations on complex objects. Apparently, employing just a number of processors is not a panacea for our database problem. The sheer horse power of machines does not help very much when data synchronization and event serialization requirements play a major role during object handling. What are the critical hardware architecture properties? How can the existing MIPS be best utilized for the data management functions when processing complex objects? To answer these questions and related issues, we discuss different kinds of architectures combining multiple processors: loosely-, tightly-, and closely-coupled. Furthermore, we consider parallelism at different levels of abstraction: the distribution of (sub-)queries or the decomposition of such queries and their concurrent evaluation at an inter-or intra-object level. Finally, we give some thoughts as to the problems of load control and transaction management