Siddhisanket Raskar
ABSTRACT
This work proposes a novel algorithm and Integer Linear Programming (ILP) formulation to optimize the pipelined code mapping of dataflow graph under a given budget generated by optimizing compilers. The goal of this optimization technique is to maximize the throughput of dataflow software pipelining under the given budget, i.e. when the minimum number of fifo buffers needed to optimally balance the dataflow graph are not available with the system. A proposed algorithm uses a two-fold solution by combining a well-established optimal dataflow graph balancing ILP formulation which doesn't consider resource budget constraints with our proposed ILP formulation which considers resource budget constraints. Our algorithm efficiently maximizes the throughput of dataflow software pipeline under a given resource budget. Additionally, we introduce a cycle-accurate dataflow graph simulator for the evaluation of various balancing techniques. We perform an experimental evaluation of different optimizing techniques and show that our proposed novel algorithm performs relatively well compared to existing techniques.
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Index Terms
- Towards Maximum Throughput of Dataflow Software Pipeline under Resource Constraints
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