Integrated Software Pipelining
In this thesis we address the problem of integrated software pipelining for clustered VLIW architectures. The phases that are integrated and solved as one combined problem are: cluster assignment, instruction selection, scheduling, register allocation and spilling. As a first step we describe two me...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Institutionen för datavetenskap
2009
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-16170 http://nbn-resolving.de/urn:isbn:9789173936996 |
| Summary: | In this thesis we address the problem of integrated software pipelining for clustered VLIW architectures. The phases that are integrated and solved as one combined problem are: cluster assignment, instruction selection, scheduling, register allocation and spilling. As a first step we describe two methods for integrated code generation of basic blocks. The first method is optimal and based on integer linear programming. The second method is a heuristic based on genetic algorithms. We then extend the integer linear programming model to modulo scheduling. To the best of our knowledge this is the first time anybody has optimally solved the modulo scheduling problem for clustered architectures with instruction selection and cluster assignment integrated. We also show that optimal spilling is closely related to optimal register allocation when the register files are clustered. In fact, optimal spilling is as simple as adding an additional virtual register file representing the memory and have transfer instructions to and from this register file corresponding to stores and loads. Our algorithm for modulo scheduling iteratively considers schedules with increasing number of schedule slots. A problem with such an iterative method is that if the initiation interval is not equal to the lower bound there is no way to determine whether the found solution is optimal or not. We have proven that for a class of architectures that we call transfer free, we can set an upper bound on the schedule length. I.e., we can prove when a found modulo schedule with initiation interval larger than the lower bound is optimal. Experiments have been conducted to show the usefulness and limitations of our optimal methods. For the basic block case we compare the optimal method to the heuristic based on genetic algorithms. This work has been supported by The Swedish national graduate school in computer science (CUGS) and Vetenskapsrådet (VR). |
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