Abstract
While many approximate computing methods are quite application-dependent, reducing the size of the data representation used in the computation has a more general applicability. We present a tuning assistant for floating to fixed point optimization (TAFFO), an LLVM-based framework designed to assist programmers in the precision tuning of software. We discuss the framework architecture and we provide guidelines to effectively tradeoff precision to improve the time-to-solution. We evaluate our framework on a well-known approximate computing benchmark suite, AxBench, achieving a speedup on 5 out of 6 benchmarks (up to 366%) with only a limited loss in precision (<3% for all benchmarks). Contrary to most related tools, TAFFO supports both C and C++ programs. It is provided as a plugin for LLVM, a design solution that improves significantly the maintainability of the tool and its ease of use.
Daniele Cattaneo
Postdoctoral Researcher
Giovanni Agosta
Associate Professor
Giovanni Agosta, Associate Professor at Politecnico di Milano, holds a Laurea in Computer Engineering (2000) and a PhD in Information Technology (2004). His research focuses on compiler-computer architecture interaction, emphasizing performance, energy-efficiency, and security. He has authored 100+ papers, won multiple awards, and participated in 17 EU-funded projects.