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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Govindarajan, R. Hongbo Yang Amaral, J.N. Chihong Zhang Gao, G.R. |
| Copyright Year | 1968 |
| Abstract | In this paper, we address the problem of generating an optimal instruction sequence S for a Directed Acyclic Graph (DAG), where S is optimal in terms of the number of registers used. We call this the Minimum Register Instruction Sequence (MRIS) problem. The motivation for revisiting the MRIS problem stems from several modern architecture innovations/requirements that has put the instruction sequencing problem in a new context. We develop an efficient heuristic solution for the MRIS problem. This solution is based on the notion of instruction lineage-a set of instructions that can definitely share a single register. The formation of lineages exploits the structure of the dependence graph to facilitate the sharing of registers not only among instructions within a lineage, but also across lineages. Our efficient heuristics to "fuse" lineages further reduce the register requirement. This reduced register requirement results in generating a code sequence with fewer register spills. We have implemented our solution in the MIPSpro production compiler and measured its performance on the SPEC95 floating point benchmark suite. Our experimental results demonstrate that the proposed instruction sequencing method significantly reduces the number of spill loads and stores inserted in the code, by more than 50 percent in each of the benchmarks. Our approach reduces the average number of dynamic loads and stores executed by 10.4 percent and 3.7 percent, respectively. Further, our approach improves the execution time of the benchmarks on an average by 3.2 percent. In order to evaluate how efficiently our heuristics find a near-optimal solution to the MRIS problem, we develop an elegant integer linear programming formulation for the MRIS problem. Using a commercial integer linear programming solver, we obtain the optimal solution for the MRIS problem. Comparing the optimal solution from the integer linear programming tool with our heuristic solution reveals that, in a very large majority (99.2 percent) of the cases, our heuristic solution is optimal. For this experiment, we used a set of 675 dependence graphs representing basic blocks extracted from scientific benchmark programs. |
| Sponsorship | IEEE Computer Society Technical Committee on Distributed Process IEEE Computer Society Technical Committee on VLSI IEEE Technical Committee on Computer Architecture IEEE Computer Society |
| Starting Page | 4 |
| Ending Page | 20 |
| Page Count | 17 |
| File Size | 1088401 |
| File Format | |
| ISSN | 00189340 |
| Volume Number | 52 |
| Issue Number | 1 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Out of order Magnetic resonance imaging Registers Integer linear programming Parallel processing Runtime Hardware Technological innovation Production Processor scheduling |
| Content Type | Text |
| Resource Type | Article |
| Subject | Theoretical Computer Science Computational Theory and Mathematics Software Hardware and Architecture |
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