The JalapeÃño Dynamic Optimizing Compiler is a key component of the JalapeÃño Virtual Machine, a new Java Virtual Machine (JVM) designed to support efficient and scalable execution of Java applications on SMP server machines. This paper describes the design of the JalapeÃño Optimizing Compiler, and the implementation results that we have obtained thus far. To the best of our knowledge, this is the first dynamic optimizing compiler for Java that is being used in a JVM with a compile-only approach to program execution.

. We present a simple, unified approach for the analysis and optimization of object field and array element accesses in strongly typed languages, that works in the presence of object references/pointers. This approach builds on Array SSA form [14], a uniform representation for capturing control and data flow properties at the level of array elements. The techniques presented here extend previous analyses at the array element level [15] to handle both array element and object field accesses uniformly. In the first part of this paper, we show how SSA-based program analyses developed for scalars and arrays can be extended to operate on object references in a strongly typed language like Java. The extension uses Array SSA form as its foundation by modeling object references as indices into hypothetical heap arrays. In the second part of this paper, we present two new sparse analysis algorithms using the heap array representation; one identifies redundant loads, and the other ...

The Jalape~no Dynamic Optimizing Compiler is a key com-ponent of the Jalape~no Virtual Machine, a new Java 1 Vir-tual Machine (JVM) designed to support e cient and scal-able execution of Java applications on SMP server machines. This paper describes the design of the Jalape~no Optimizing Compiler, and the implementation results that we have ob-tained thus far. To the best of our knowledge, this is the rst dynamic optimizing compiler for Java that is being used in a JVM with a compile-only approach to program execution. 1