Demo Data from SIGIR 2026 / reviewers in the wild / expert
Hendrik Schmidl
dblp:285/5114
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—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 |
Emerging computing paradigms · 56% Reconfigurable computing and FPGAs · 28% Integrated circuit design · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Emerging computing paradigms
approximate computing |
0.5 | 1 | 2021 | Area-Optimized Accurate and Approximate Softcore Signed Multiplier Architectures · IEEE Trans. Computers 2021 |
Emerging computing paradigms › approximate computing
approximate multiplier |
0.5 | 1 | 2021 | Area-Optimized Accurate and Approximate Softcore Signed Multiplier Architectures · IEEE Trans. Computers 2021 |
Reconfigurable computing and FPGAs
FPGA arithmetic |
0.5 | 1 | 2021 | Area-Optimized Accurate and Approximate Softcore Signed Multiplier Architectures · IEEE Trans. Computers 2021 |
Electronic design automation › design optimization
area optimization |
0.1 | 1 | 2021 | Area-Optimized Accurate and Approximate Softcore Signed Multiplier Architectures · IEEE Trans. Computers 2021 |
Integrated circuit design
digital circuit design |
0.1 | 1 | 2021 | Area-Optimized Accurate and Approximate Softcore Signed Multiplier Architectures · IEEE Trans. Computers 2021 |
Methods — techniques the papers use, named apart from their topics
RTL modeling · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Area-Optimized Accurate and Approximate Softcore Signed Multiplier ArchitecturesabstractMultiplication is one of the most extensively used arithmetic operations in a wide range of applications. In order to provide resource-efficient and high-performance multipliers, previous works have proposed different designs of accurate and approximate multipliers-mainly for ASIC-based systems. However, the architectural differences between ASICs- and FPGA-based systems limit the effectiveness of these multipliers for FPGA-based systems. Moreover, most of these multiplier designs are valid only for unsigned numbers. To bridge this gap, we propose a novel implementation technique for designing resource-efficient and low-power accurate and approximate signed multipliers which are optimized for FPGA-based systems. Compared to Vivado's area-optimized multiplier IPs, the designs obtained using our proposed technique occupy 47 to 63 percent less area (Lookup Tables). To accelerate further research in this direction and reproduce the presented results, the RTL and behavioral models of our proposed methodology are available as an open-source library.11.Online. [Available]: https://cfaed.tu-dresden.de/pd-downloads. Salim Ullah, Hendrik Schmidl, Siva Satyendra Sahoo, Semeen Rehman, Akash Kumar 0001 |
IEEE Trans. Computers | 2 |