EDBT 2026 Demo / reviewers in the wild / expert
Lazar Saranovac
dblp:62/9722 · also Lazar V. Saranovac
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0002-6823-1855ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3Software engineering, systems software and programming languages · 2Graphics, computer vision, multimedia, augmented reality and games · 1
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 |
Reconfigurable computing and FPGAs · 50% Processor architecture and microarchitecture · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Reconfigurable computing and FPGAs
coarse-grained reconfigurable architecture |
0.2 | 1 | 2013 | Selective Flexibility: Creating Domain-Specific Reconfigurable Arrays · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2013 |
Processor architecture and microarchitecture › special-purpose processor › application-specific processor design
customizable processor |
0.2 | 1 | 2013 | Selective Flexibility: Creating Domain-Specific Reconfigurable Arrays · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2013 |
Reconfigurable computing and FPGAs › coarse-grained reconfigurable architecture
domain-specific reconfigurable array |
0.2 | 1 | 2013 | Selective Flexibility: Creating Domain-Specific Reconfigurable Arrays · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2013 |
Processor architecture and microarchitecture › instruction set architecture
instruction set extension |
0.2 | 1 | 2013 | Selective Flexibility: Creating Domain-Specific Reconfigurable Arrays · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2013 |
Methods — techniques the papers use, named apart from their topics
datapath merging · 0.2application-specific instruction set extension · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Enhanced local tone mapping for detail preserving reproduction of high dynamic range images
Dragomir M. El Mezeni, Lazar Saranovac |
J. Vis. Commun. Image Represent. | 2 |
| 2017 | Formal model for system-level power management designabstractIn this paper we present a new formal model, called p-FSM, for system-level power management design. The p-FSM is a modular, compositional, hierarchical, and unified model for hardware and software components. The model encapsulates power management control mechanisms, operating states and properties of a component that affect power, energy and thermal aspects of the system. Inter-component dependencies are modeled through a component-based interface. By connecting multiple p-FSMs we gradually compose the model of the whole system which ensures correct-by-construction system-level control sequencing. The model can also be used to formally verify the functional correctness of the power management design. Mirela Simonovic, Vojin Zivojnovic, Lazar Saranovac |
DATE | 3 |
| 2013 | Selective Flexibility: Creating Domain-Specific Reconfigurable ArraysabstractHistorically, hardware acceleration technologies have either been application-specific, therefore lacking in flexibility, or fully programmable, thereby suffering from notable inefficiencies on an application-by-application basis. To address the growing need for domain-specific acceleration technologies, this paper describes a design methodology (i) to automatically generate a domain-specific coarse-grained array from a set of representative applications and (ii) to introduce limited forms of architectural generality to increase the likelihood that additional applications can be successfully mapped onto it. In particular, coarse-grained arrays generated using our approach are intended to be integrated into customizable processors that use application-specific instruction set extensions to accelerate performance and reduce energy; rather than implementing these extensions using application-specific integrated circuit (ASIC) logic, which lacks flexibility, they can be synthesized onto our reconfigurable array instead, allowing the processor to be used for a variety of applications in related domains. Results show that our array is around 2× slower and 15× larger than an ultimately efficient ASIC implementation, and thus far more efficient than fieldprogrammable gate arrays (FPGAs), which are known to be 3-4× slower and 20-40× larger. Additionally, we estimate that our array is usually around 2× larger and 2× slower than an accelerator synthesized using traditional datapath merging, which has, if any, very limited flexibility beyond the design set of DFGs. Mirjana Stojilovic, David Novo, Lazar Saranovac, Philip Brisk, Paolo Ienne |
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. | 3 |
| 2012 | Selective flexibility: Breaking the rigidity of datapath mergingabstractHardware specialization is often the key to efficiency for programmable embedded systems, but comes at the expense of flexibility. This paper combines flexibility and efficiency in the design and synthesis of domain-specific datapaths. We merge all individual paths from the Data Flow Graphs (DFGs) of the target applications, leading to a minimal set of required resources; this set is organized into a column of physical operators and cloned, thus generating a domain-specific rectangular lattice. A bus-based FPGA-style interconnection network is then generated and dimensioned to meet the needs of the applications. Our results demonstrate that the lattice has good flexibility: DFGs that were not used as part of the datapath creation phase can be mapped onto it with high probability. Compared to an ASIC design of a single DFG, the speed of our domain-specific coarse-grained reconfigurable datapath is degraded by a factor up to 2×, compared to 3-4× for an FPGA; similarly, our lattice is up to 10× larger than an ASIC, compared to 20-40× for an FPGA. We estimate that our array is up to 6× larger than an ASIC accelerator, which is synthesized using datapath merging and has limited or null generality. Mirjana Stojilovic, David Novo, Lazar Saranovac, Philip Brisk, Paolo Ienne |
DATE | 3 |