Demo Data from VLDB 2026 / reviewers in the wild / expert
Vinicius Possani
dblp:327/2127
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation
logic synthesis |
0.6 | 1 | 2022 | Improving LUT-based optimization for ASICs · DAC 2022 |
Electronic design automation › logic synthesis › FPGA synthesis
LUT-based optimization |
0.6 | 1 | 2022 | Improving LUT-based optimization for ASICs · DAC 2022 |
Electronic design automation › logic synthesis
technology mapping |
0.6 | 1 | 2022 | Improving LUT-based optimization for ASICs · DAC 2022 |
Methods — techniques the papers use, named apart from their topics
flowmap · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Improving LUT-based optimization for ASICsabstractLUT-based optimization techniques are finding new applications in synthesis of ASIC designs. Intuitively, packing logic into LUTs provides a better balance between functionality and structure in logic optimization. On this basis, the LUT-engine framework [1] was introduced to enhance the ASIC synthesis. In this paper, we present key improvements, at both algorithmic and flow levels, making a much stronger LUT-engine. We restructure the flow of LUT-engine, to benefit from a heterogeneous mixture of LUT sizes, and revisit its requirements for maximum scalability. We propose a dedicated LUT mapper for the new flow, based on FlowMap, natively balancing LUT-count and NAND2-count for a wide range LUT sizes. We describe a specialized Boolean factoring technique, exploiting the fanin bounds in LUT networks, resulting in a very fast LUT-based AIG minimization. By using the proposed methodology, we improve 9 of the best area results in the ongoing EPFL synthesis competition. Integrated in a complete EDA flow for ASICs, the new LUT-engine performs well on a set of 87 benchmarks: -4.60% area and -3.41% switching power at +5% runtime, compared to the baseline flow without LUT-based optimizations, and -3.02% area and -2.54% switching power with -1% runtime, compared to the original LUT-engine. Walter Lau Neto, Luca G. Amarù, Vinicius Possani, Patrick Vuillod, Jiong Luo, Alan Mishchenko, Pierre-Emmanuel Gaillardon |
DAC | 3 |