Value prediction in VLIW machines

The performance of VLIW architectures is dependent on the capability of the compiler to detect and exploit instruction-level parallelism during instruction scheduling. To exploit the detected parallelism, instructions are reordered to reduce the length of the code schedule and minimize the cycle count for execution. Code reordering is limited by the dependencies among instructions arising from both control flow and data flow. In this paper, we present the design of a VLIW architecture that uses value prediction to remove data dependencies and improve the instruction schedule. Our architecture consists of two execution engines, one for executing the original VLIW code, and the other for executing compensation code after a misprediction. Any code executed due to mispredictions is executed in parallel with the VLIW instructions. The instruction set and hardware of a traditional VLIW machine are modified accordingly to support this type of concurrent execution. The efficacy of the proposed architecture is demonstrated by implementing the prediction model in the Trimaran compiler infrastructure and studying the speedups that result due to the parallel execution of compensation code.