Register allocation and spilling using the expected distance heuristic
| dc.contributor.author | Burroughs, Ivan Neil | |
| dc.contributor.supervisor | Horspool, Nigel | |
| dc.date.accessioned | 2016-04-12T16:43:09Z | |
| dc.date.available | 2016-04-12T16:43:09Z | |
| dc.date.copyright | 2016 | en_US |
| dc.date.issued | 2016-04-12 | |
| dc.degree.department | Department of Computer Science | |
| dc.degree.level | Doctor of Philosophy Ph.D. | en_US |
| dc.description.abstract | The primary goal of the register allocation phase in a compiler is to minimize register spills to memory. Spills, in the form of store and load instructions, affect execution time as the processor must wait for the slower memory system to respond. Deciding which registers to spill can benefit from execution frequency information yet when this information is available it is not fully utilized by modern register allocators. We present a register allocator that fully exploits profiling information to mini- mize the runtime costs of spill instructions. We use the Furthest Next Use heuristic, informed by branch probability information to decide which virtual register to spill when required. We extend this heuristic, which under the right conditions can lead to the minimum number of spills, to the control flow graph by computing Expected Distance to next use. The furthest next use heuristic, when applied to the control flow graph, only par- tially determines the best placement of spill instructions. We present an algorithm for optimizing spill instruction placement in the graph that uses block frequency infor- mation to minimize execution costs. Our algorithm quickly finds the best placements for spill instructions using a novel method for solving placement problems. We evaluate our allocator using both static and dynamic profiling information for the SPEC CINT2000 benchmark and compare it to the LLVM allocator. Targeting the ARMv7 architecture, we find average reductions in numbers of store and load instructions of 36% and 50%, respectively, using static profiling and 52% and 52% using dynamic profiling. We have also seen an overall improvement in benchmark speed. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/7107 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | Compilers | en_US |
| dc.subject | Register Allocation | en_US |
| dc.subject | Spilling | en_US |
| dc.subject | Expected Distance | en_US |
| dc.title | Register allocation and spilling using the expected distance heuristic | en_US |
| dc.type | Thesis | en_US |