<p>This master’s thesis examines the possibility to heuristically optimise instruction cache performance in a Just-In-Time (JIT) compiler. </p><p>Programs that do not fit inside the cache all at once may suffer from cache misses as a result of frequently executed code segments competing for the same cache lines. A new heuristic algorithm LHCPA was created to place frequently executed code segments to avoid cache conflicts between them, reducing the overall cache misses and reducing the performance bottlenecks. Set-associative caches are taken into consideration and not only direct mapped caches. </p><p>In Ahead-Of-Time compilers (AOT), the problem with frequent cache misses is often avoided by using call graphs derived from profiling and more or less complex algorithms to estimate the performance for different placements approaches. This often results in heavy computation during compilation which is not accepted in a JIT compiler. </p><p>A case study is presented on an Alpha processor and an at Ericsson developed JIT Compiler. The results of the case study shows that cache performance can be improved using this technique but also that a lot of other factors influence the result of the cache performance. Such examples are whether the cache is set-associative or not; and especially the size of the cache highly influence the cache performance.</p>

This master’s thesis examines the possibility to heuristically optimise instruction cache performance in a Just-In-Time (JIT) compiler. Programs that do not fit inside the cache all at once may suffer from cache misses as a result of frequently executed code segments competing for the same cache lines. A new heuristic algorithm LHCPA was created to place frequently executed code segments to avoid cache conflicts between them, reducing the overall cache misses and reducing the performance bottlenecks. Set-associative caches are taken into consideration and not only direct mapped caches. In Ahead-Of-Time compilers (AOT), the problem with frequent cache misses is often avoided by using call graphs derived from profiling and more or less complex algorithms to estimate the performance for different placements approaches. This often results in heavy computation during compilation which is not accepted in a JIT compiler. A case study is presented on an Alpha processor and an at Ericsson developed JIT Compiler. The results of the case study shows that cache performance can be improved using this technique but also that a lot of other factors influence the result of the cache performance. Such examples are whether the cache is set-associative or not; and especially the size of the cache highly influence the cache performance.