Automated Synthesis of Streaming Transfer Level Hardware Designs

Abstract

As modern field-programmable gate arrays (FPGA) enable high computing performance and efficiency, their programming with low-level hardware description languages is time-consuming and remains a major obstacle to their adoption. High-level synthesis compilers are able to produce register-transfer-level (RTL) designs from C/C++ algorithmic descriptions, but despite allowing significant design-time improvements, these tools are not always able to generate hardware designs that compare to handmade RTL designs. In this article, we consider synthesis from an intermediate-level (IL) language that allows the description of algorithmic state machines handling connections between streaming sources and sinks. However, the interconnection of streaming sources and sinks can lead to cyclic combinational relations, resulting in undesirable behaviors or un-synthesizable designs. We propose a functional-level methodology to automate the resolution of such cyclic relations into acyclic combinational functions. The proposed IL synthesis methodology has been applied to the design of pipelined floating-point cores. The results obtained show how the proposed IL methodology can simplify the description of pipelined architectures while enabling performances that are close to those achievable through an RTL design methodology.

MIP formulations for induced graph optimization problems: a tutorial

“…Induced forests and feedback vertex set problems have been extensively studied in the literature. Applications can be found in several domains, such as program verification (Shamir, 1979), deadlock prevention and resolution in operating systems (Wang et al., 1985; Carneiro et al., 2019), constraint satisfaction and bayesian inference (Dechter and Pearl, 1988; Bar‐Yehuda et al., 1998), the study of monopolies in distributed systems (Peleg, 1998), combinatorial circuit design (Bafna et al., 1999), optical networks (Kleinberg and Kumar, 2001), parallel systems and distributed computing (Bossard, 2014), complex networks (Zañudo et al., 2017), hardware description languages and compilation (Daigneault and David, 2018), automated systems for storage and retrieval (Gharehgozli et al., 2021), as well as biology systems and bioinformatics (Aracena et al., 2021).…”