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Compiler Research at the Indian Institute of Science Bangalore, India. Y.N. Srikant Professor and Chairman Department of Computer Science and Automation Indian Institute of Science srikant@csa.iisc.ernet.in. Past Research. Automatic generation of incremental parsers and semantic analyzers
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Compiler Research at the Indian Institute of ScienceBangalore, India Y.N. Srikant Professor and Chairman Department of Computer Science and Automation Indian Institute of Science srikant@csa.iisc.ernet.in
Past Research • Automatic generation of incremental parsers and semantic analyzers • Optimizer generator • Machine code generation with top-down tree pattern matching • New algorithm for partial redundancy elimination • Automatic parallelization for distributed memory machines • Automatic data partitioning based on genetic algorithms (for DMMs)
Current Research Areas • Code Generator Generators • Instruction Scheduling • Power-aware compilation • Just-In-Time compilation
Code Generator Generators • Emphasis on generating efficient code generators from machine descriptions • Uses new tree pattern matching alogorithm based on LR-parsing (in-house) • Integrated into TRIMARAN and is based on LCODE intermediate code • Tried on DSP (Texas Instr.) and Itanium • Faculty member: Priti Shankar
Instruction Scheduling • Faculty members • R. Govindarajan, Priti Shankar and Y.N. Srikant • New approaches for VLIW and Superscalar architectures • Integer linear programming • Co-scheduling hardware and software pipelines
Instruction Scheduling (contd.) • Instruction scheduling for clustered DSP architectures • Integrated scheduling combining clustering and scheduling • Graph matching based scheduling • Integrated into SUIF • Experiments with TI 32064X
Power Aware Compilation • Transition-aware scheduling • Reduces the number of transitions from active to low-power and vice-versa • Saves energy • With XScale, XTREM, and gcc • Experiments with heterogeneous interconnects in clustered VLIW architectures • Two interconnects, one with high speed and high power requirement, another with lower speed and lower power requirement • Experiments with TRIMARAN (suitably modified)
Power Aware Compilation (contd.) • Experiments with Object cache • Separate cache for objects • Combination saves energy and is as fast as a general purpose cache • Use of static analysis and profiling to classify objects as long living and short living • A Framework for writing power aware applications with ECOS • Hooks into the OS • ??
JIT Compilation • An efficient JIT compiler for .NET CLI on ROTOR • Profile-guided optimizations • ‘Cluster and Collect’ concurrent garbage collector • Detects long-living clusters of objects by profiling and static analysis • Allocates them in a separate mature object space • Stack allocation for scoped objects • Architectural innovations to speedup profile collection • Low profiling speed is the bottleneck with profile-guided optimizations • Most common types of profiling can be carried out
Thank You Questions?