Specialized hardware accelerators are becoming important for more and more applications. Thanks to specialization, they can achieve high performance and energy efficiency but their design is complex and time consuming. This problem is exacerbated when large amounts of data must be processed, like in modern big data and machine learning applications. The designer has not only to optimize the accelerator logic but also produce efficient memory architectures. To simplify this process, we propose a multi-level compilation flow that specializes a domain-specific memory template to match data, application, and technology requirements.
翻译:专门硬件加速器对越来越多的应用变得日益重要。 由于专业化,它们可以实现高性能和能源效率,但设计既复杂又耗时。当必须处理大量数据时,这一问题就更加严重,如在现代大数据和机器学习应用程序中。设计者不仅要优化加速器逻辑,还要生成高效的记忆结构。为了简化这一过程,我们建议了一个多层次的汇编流程,专门设计一个特定领域的存储模板,以匹配数据、应用和技术要求。