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In this paper, we present two symbiotic optimizations to optimize recursivetask parallel (RTP) programs by reducing the task creation and terminationoverheads. Our first optimization Aggressive Finish-Elimination (AFE) helpsreduce the redundant join operations to a large extent. The second optimizationDynamic Load-Balanced loop Chunking (DLBC) extends the prior work on loopchunking to decide on the number of parallel tasks based on the number ofavailable worker threads, at runtime. Further, we discuss the impact ofexceptions on our optimizations and extend them to handle RTP programs that maythrow exceptions. We implemented DCAFE (= DLBC+AFE) in the X10v2.3 compiler andtested it over a set of benchmark kernels on two different hardwares (a 16-coreIntel system and a 64-core AMD system). With respect to the base X10 compilerextended with loop-chunking of Nandivada et al [Nandivada etal.(2013)Nandivada, Shirako, Zhao, and Sarkar](LC), DCAFE achieved a geometricmean speed up of 5.75x and 4.16x on the Intel and AMD system, respectively. Wealso present an evaluation with respect to the energy consumption on the Intelsystem and show that on average, compared to the LC versions, the DCAFEversions consume 71.2% less energy.

DCAFE: Dynamic load-balanced loop Chunking & Aggressive Finish Elimination for Recursive Task Parallel Programs