Lucas Ramirez

dblp:398/7100 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0008-5656-4047ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 67% Reconfigurable computing and FPGAs · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Reconfigurable computing and FPGAs
coarse-grained reconfigurable architecture
0.912025
FRIDA: Reconfigurable Arrays for Dynamically Scheduled High-Level Synthesis · FPGA 2025
Electronic design automation › high-level synthesis
dynamically scheduled high-level synthesis
0.912025
FRIDA: Reconfigurable Arrays for Dynamically Scheduled High-Level Synthesis · FPGA 2025
Electronic design automation
high-level synthesis
0.912025
FRIDA: Reconfigurable Arrays for Dynamically Scheduled High-Level Synthesis · FPGA 2025

Methods — techniques the papers use, named apart from their topics

bus-based interconnect · 0.9FPGA-style routing · 0.9
YearPublicationVenuePosition
2025 FRIDA: Reconfigurable Arrays for Dynamically Scheduled High-Level Synthesis
abstract
Reconfigurable computing fabrics include FPGAs and CGRAs. FPGAs offer flexible bit-level reconfigurability and can map almost any program via high-level synthesis (HLS) compilers, but they incur high area and speed overheads compared to ASICs. CGRAs, in contrast, provide ASIC-like performance but limited flexibility, typically supporting only feedforward programs with unambiguous memory accesses, far from the capabilities of HLS compilers. This work introduces a new class of reconfigurable arrays inspired by modern dynamically scheduled HLS (DHLS) tools. Unlike traditional HLS, DHLS compilers no longer produce explicit state machines, eliminating the need for look-up tables. Instead, they delegate scheduling decisions to a set of coarse-grained primitives. Our arrays leverage these primitives as processing elements and combine FPGA-style interconnect topology for high routing flexibility with CGRA-like bus-based interconnect. We present a framework to explore these arrays and evaluate a preliminary architecture using DHLS benchmarks. The results show an average of ~2× speed improvement, but unfortunately only a ~20% area reduction compared to an FPGA implemented on the same technology node.
Louis Coulon, Lucas Ramirez, Jason Helge Anderson, Mirjana Stojilovic, Paolo Ienne
FPGA2