By James Larus (auth.), Rajiv Gupta (eds.)
This publication constitutes the refereed lawsuits of the nineteenth foreign convention on Compiler development, CC 2010, held in Paphos, Cyprus, in March 2010, as a part of ETAPS 2010, the Joint ecu meetings on concept and perform of software program. Following an intensive overview procedure, sixteen learn papers have been chosen from fifty six submissions. subject matters coated comprise optimization innovations, software ameliorations, software research, sign up allocation, and high-performance structures.
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Additional info for Compiler Construction: 19th International Conference, CC 2010, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2010, Paphos, Cyprus, March 20-28, 2010. Proceedings
8. Algorithm 1: Compute RecursivePredicate and ExitPredicate 4. Pick an unused SSA name for the RecursiveP redicate. 5. Convert φ-nodes to gating function μ. 6. Insert (RP )[T ]RP = .... at the very beginning of loop header where RP is the SSA name picked in the previous step and it is assigned to the computed RecursiveP redicate by converting all the predicate variables in the computed predicate to future form. 7. Convert every instruction in the header to recursive form using RP and delete the back edges and branches.
At the register allocation stage, the goal is to minimize live range of variables in the resulting CFG. So we must take into account diﬀerent optimality criteria for diﬀerent conversion stages. The basic algorithm to transform RFPF back to CFG consists of three steps: 1. Reorder RFPF in a way that no future values occur by pushing-down or moving-up instructions, which forms an initial instruction list. 2. Group instructions with identical predicates together. Such grouping reduces the multiple node insertions for a branch condition and forms the loop structures.
Java just-intime compiler and virtual machine improvements for server and middleware applications. In: Conference on Virtual Machine Research and Technology Symposium (VM), San Jose, CA, USA, pp. 12–12 (2004) 9. : PerfExplorer: A performance data mining framework for large-scale parallel computing. In: ACM/IEEE Conference on Supercomputing (SC), Seattle, WA, USA, p. 41 (2005) 10. : HP Caliper: A framework for performance analysis tools. IEEE Concurrency 8(4), 64–71 (2000) 11. IBM Corporation.