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Pub/Speeding up dynamic compilation: concurrent and parallel dynamic compilation (PhD)


The main challenge faced by a dynamic compilation system is to detect and translate frequently executed program regions into highly efficient native code as fast as possible. To efficiently reduce dynamic compilation latency, a dynamic compilation system must improve its workload throughput, i.e. compile more application hotspots per time. As time for dynamic compilation adds to the overall execution time, the dynamic compiler is often decoupled and operates in a separate thread independent from the main execution loop to reduce the overhead of dynamic compilation. This thesis proposes innovative techniques aimed at effectively speeding up dynamic compilation. The first contribution is a generalised region recording scheme optimised for program representations that require dynamic code discovery (e.g. binary program representations). The second contribution reduces dynamic compilation cost by incrementally compiling several hot regions in a concurrent and parallel task farm. Altogether the combination of generalised light-weight code discovery, large translation units, dynamic work scheduling, and concurrent and parallel dynamic compilation ensures timely and efficient processing of compilation workloads. Compared to state-of-the-art dynamic compilation approaches, speedups of up to 2.08 are demonstrated for industry standard benchmarks such as BioPerf, Spec CPU 2006, and EEMBC. Next, innovative applications of the proposed dynamic compilation scheme to speed up architectural and micro-architectural performance modelling are demonstrated. The main contribution in this context is to exploit runtime information to dynamically generate optimised code that accurately models architectural and micro-architectural components. Consequently, compilation units are larger and more complex resulting in increased compilation latencies. Large and complex compilation units present an ideal use case for our concurrent and parallel dynamic compilation infrastructure. We demonstrate that our novel micro-architectural performance modelling is faster than state-of-the-art Fpga-based simulation, whilst providing the same level of accuracy.