The effect of branch prediction on the efficiency of interpreters

OData support
Supervisor:
Dr. Horváth Gábor
Department of Networked Systems and Services

Advanced processors released these days use a technique called instruction pipelining to improve instruction throughput. However pipelining introduces a set of problems, one of them being the control hazard. To resolve control hazards the outcome and the target address of the branches must be predicted. According to my measurements every 6th--10th instructions are affected, thus even a small improvement can make a huge difference in the execution time of programs. In my thesis I measure some branch prediction algorithms in use, and benchmark them using data gathered from real life applications.

Recently we saw an increasing use of programming languages that do not compile to native code (for example Java, Python, Lua, JavaScript, Ruby, ...), but instead need an extra program (the runtime environment) to run them, and

some of them use interpreters to execute code. By investigating the Lua interpreter I show how much improvement in speed can be achieved by just using a better branch predictor in the CPU.

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