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No Bit Left Behind

其他書名	The Limits of Heap Data Compression : (Extended Version TR-08-17)
出版	Computer Science Department, University of Texas at Austin, 2008
URL	http://books.google.com.hk/books?id=wLjsjwEACAAJ&hl=&source=gbs_api

註釋On the one hand, the high cost of memory continues to drive demand for memory efficiency on embedded and general purpose computers. On the other hand, programmers are increasingly turning to managed languages like Java for their functionality, programmability, and reliability. Managed languages, however, are not known for their memory efficiency, creating a tension between productivity and performance. This paper examines the sources and types of memory inefficiencies in a set of Java benchmarks. Although prior work has proposed specific heap data compression techniques, they are typically restricted to one model of inefficiency. This paper generalizes and quantitatively compares previously proposed memory-saving approaches and idealized heap compaction. It evaluates a variety of models based on strict and deep object equality, field value equality, removing bytes that are zero, and compressing fields and arrays with a limited number and range of values. The results show that substantial memory reductions are possible in the Java heap. These results demonstrate that future work should be able to combine a high productivity programming language with memory efficiency.