Lookup Cost Research Articles

Selective specialization for object-oriented languages

Dynamic dispatching is a major source of run-time overhead in object-oriented languages, due both to the direct cost of method lookup and to the indirect effect of preventing other optimizations. To reduce this overhead, optimizing compilers for object-oriented languages analyze the classes of objects stored in program variables, with the goal of bounding the possible classes of message receivers enough so that the compiler can uniquely determine the target of a message send at compile time and replace the message send with a direct procedure call. Specialization is one important technique for improving the precision of this static class information: by compiling multiple versions of a method, each applicable to a subset of the possible argument classes of the method, more precise static information about the classes of the method's arguments is obtained. Previous specialization strategies have not been selective about where this technique is applied, and therefore tended to significantly increase compile time and code space usage, particularly for large applications. In this paper, we present a more general framework for specialization in object-oriented languages and describe a goal directed specialization algorithm that makes selective decisions to apply specialization to those cases where it provides the highest benefit. Our results show that our algorithm improves the performance of a group of sizeable programs by 65% to 275% while increasing compiled code space requirements by only 4% to 10%. Moreover, when compared to the previous state-of-the-art specialization scheme, our algorithm improves performance by 11% to 67% while simultaneously reducing code space requirements by 65% to 73%.

Caching Hints in Distributed Systems

Caching reduces the average cost of retrieving data by amortizing the lookup cost over several references to the data. Problems with maintaining strong cache consistency in a distributed system can be avoided by treating cached information as hints. A new approach to managing caches of hints suggests maintaining a minimum level of cache accuracy, rather than maximizing the cache hit ratio, in order to guarantee performance improvements. The desired accuracy is based on the ratio of lookup costs to the costs of detecting and recovering from invalid cache entries. Cache entries are aged so that they get purged when their estimated accuracy falls below the desired level. The age thresholds are dictated solely by clients' accuracy requirements instead of being suggested by data storage servers or system administrators.