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.

中文翻译：

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TAFFO：浮点到定点优化的调优助手

虽然许多近似计算方法都非常依赖于应用程序，但减少计算中使用的数据表示的大小具有更普遍的适用性。我们提出了一个用于浮点到定点优化 (TAFFO) 的调优助手，这是一个基于 LLVM 的框架，旨在帮助程序员精确调优软件。我们讨论了框架架构，并提供了有效权衡精度以缩短解决方案时间的指南。我们在著名的近似计算基准套件 AxBench 上评估我们的框架，在 6 个基准测试中的 5 个（高达 366%）上实现了加速，而精度损失有限（所有基准测试均小于 3%）。与大多数相关工具相反，TAFFO 支持 C 和 C++ 程序。它作为 LLVM 的插件提供，