1. Conrad Benham 20001 Java Opcode and Runtime Data Analysis By: Conrad Benham Supervisor: Professor Arthur Sale

2. Conrad Benham 20002 Project Goals To collect data on Java’s: Opcodes, Runtime System and Create a program to automate this. These statistics will be used by Professor Sale to create an optimised Hardware Java Virtual Machine (JVM).

3. Conrad Benham 20003 Why do this? - Competitive Analysis Presently there are few JVMs implemented in hardware. Existing implementations rarely have published documented to the level necessary for advanced research. Java statistics are often difficult to obtain or sketchy in detail.

4. Conrad Benham 20004 Why do this? - Research Analysis Statistics will identify most common opcodes. Allows hardware developers to focus on optimising a specific sub-set of the opcodes. Findings will be published to help other research efforts. Presently there are few tools which collect data of this kind.

5. Conrad Benham 20005 So how does Java work? Java Source Code Created by Java Programmer Java Compiler Produces Java Byte Codes Platform Independent JVM Runs Java Byte Codes Go to Sun Microsystems’ Java web site at: www.java.sun.com FOR MORE INFO...

6. Conrad Benham 20006 What are we looking for? Static Data collected from the byte codes. does not change during execution time. will change at compile time. Dynamic Data collected at runtime. will change at runtime (depending on inputs to a program).

7. Conrad Benham 20007 Static Data Includes data found in Java class files e.g. the iadd instruction which adds two integer operands on the operand stack together and pushes the result back on the stack. Branching Instructions The offset of instructions resulting from the conditional statements (i.e. if, while, switch, try).

8. Conrad Benham 20008 Types of Branching Instruction Forward i.e. if, else, switch and try. Backward i.e. loops such as for and while

9. Conrad Benham 20009 Dynamic Data Includes runtime analysis e.g. average loop iterations, processor usage, memory usage. analysing feasibility of using registers, efficient heap allocation/de-allocation and garbage collection routines.

10. Conrad Benham 200010 Analysis Benchmarks There are a number of benchmark suites available: Including the Dhrystone and Whetstone benchmarks Benchmark code must be: representative of most Java applications, they must follow the typical programmers coding style able to test a JVM in terms of of how much system resources it uses (e.g processor usage and memory usage).

11. Conrad Benham 200011 Method of Collection Static Data Source Code Compilation Class File Disassembly File Parsing Dynamic Data Not finalised Memory usage patterns Execution times Other performance issues

12. Conrad Benham 200012 Demonstration

13. Conrad Benham 200013 Conclusion Relatively few organisations have collected data on Java, the emphasis is on code optimisation. The main aim of this project is to create and collect reusable components, data and statistics for other research. Comments and questions.