Demo Data from EDBT 2026 / reviewers in the wild / expert
Florian Glaser
dblp:147/4590
· DBLP profile ↗
4ranked-venue papers
4as first author
1since 2021 · last 2021
0000-0002-3936-7366ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 4 · 4 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author
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 |
Processor architecture and microarchitecture · 38% Hardware accelerators and domain-specific architectures · 38% Energy-efficient computing · 12% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Processor architecture and microarchitecture › clustered architecture
cluster-based multiprocessor |
0.5 | 1 | 2021 | Energy-Efficient Hardware-Accelerated Synchronization for Shared-L1-Memory Multiprocessor Clusters · IEEE Trans. Parallel Distributed Syst. 2021 |
Energy-efficient computing › voltage scaling
near-threshold computing |
0.1 | 1 | 2021 | Energy-Efficient Hardware-Accelerated Synchronization for Shared-L1-Memory Multiprocessor Clusters · IEEE Trans. Parallel Distributed Syst. 2021 |
Methods — techniques the papers use, named apart from their topics
hardware-accelerated synchronization · 0.5fine-grain power management · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Energy-Efficient Hardware-Accelerated Synchronization for Shared-L1-Memory Multiprocessor ClustersabstractThe steeply growing performance demands for highly power- and energy-constrained processing systems such as end-nodes of the Internet-of-Things (IoT) have led to parallel near-threshold computing (NTC), joining the energy-efficiency benefits of low-voltage operation with the performance typical of parallel systems. Shared-L1-memory multiprocessor clusters are a promising architecture, delivering performance in the order of GOPS and over 100 GOPS/W of energy-efficiency. However, this level of computational efficiency can only be reached by maximizing the effective utilization of the processing elements (PEs) available in the clusters. Along with this effort, the optimization of PE-to-PE synchronization and communication is a critical factor for performance. In this article, we describe a light-weight hardware-accelerated synchronization and communication unit (SCU) for tightly-coupled clusters of processors. We detail the architecture, which enables fine-grain per-PE power management, and its integration into an eight-core cluster of RISC-V processors. To validate the effectiveness of the proposed solution, we implemented the eight-core cluster in advanced 22 nm FDX technology and evaluated performance and energy-efficiency with tunable microbenchmarks and a set of real-life applications and kernels. The proposed solution allows synchronization-free regions as small as 42 cycles, over 41× smaller than the baseline implementation based on fast test-and-set access to L1 memory when constraining the microbenchmarks to 10 percent synchronization overhead. When evaluated on the real-life DSP-applications, the proposed SCU improves performance by up to 92 and 23 percent on average and energy efficiency by up to 98 and 39 percent on average. Florian Glaser, Giuseppe Tagliavini, Davide Rossi 0001, Germain Haugou, Qiuting Huang, Luca Benini |
IEEE Trans. Parallel Distributed Syst. | 1 |
| 2019 | Hardware-Accelerated Energy-Efficient Synchronization and Communication for Ultra-Low-Power Tightly Coupled ClustersabstractParallel ultra low power computing is emerging as an enabler to meet the growing performance and energy efficiency demands in deeply embedded systems such as the end-nodes of the internet-of-things (IoT). The parallel nature of these systems however adds a significant degree of complexity as processing elements (PEs) need to communicate in various ways to organize and synchronize execution. Naive implementations of these central and non-trivial mechanisms can quickly jeopardize overall system performance and limit the achievable speedup and energy efficiency. To avoid this bottleneck, we present an event-based solution centered around a technology-independent, light-weight and scalable (up to 16 cores) synchronization and communication unit (SCU) and its integration into a shared-memory multicore cluster. Careful design and tight coupling of the SCU to the data interfaces of the cores allows to execute common synchronization procedures with a single instruction. Furthermore, we present hardware support for the common barrier and lock synchronization primitives with a barrier latency of only eleven cycles, independent of the number of involved cores. We demonstrate the efficiency of the solution based on experiments with a post-layout implementation of the multicore cluster in a 22 nm CMOS process where the SCU constitutes less than 2 % of area overhead. Our solution supports parallel sections as small as 100 or 72 cycles with a synchronization overhead of just 10 %, an improvement of up to 14× or 30× with respect to cycle count or energy, respectively, compared to a test-and-set based implementation. Florian Glaser, Germain Haugou, Davide Rossi 0001, Qiuting Huang, Luca Benini |
DATE | 1 |
| 2018 | An 826 MOPS, 210uW/MHz Unum ALU in 65 nmabstractTo overcome the limitations of conventional floating-point number formats, an interval arithmetic and variable-width storage format called universal number (unum) has been recently introduced [1]. This paper presents the first (to the best of our knowledge) silicon implementation measurements of an application-specific integrated circuit (ASIC) for unum floating-point arithmetic. The designed chip includes a 128-bit wide unum arithmetic unit to execute additions and subtractions, while also supporting lossless (for intermediate results) and lossy (for external data movements) compression units to exploit the memory usage reduction potential of the unum format. Our chip, fabricated in a 65 nm CMOS process, achieves a maximum clock frequency of 413 MHz at 1.2 V with an average measured power of 210uW/MHz. Florian Glaser, Stefan Mach, Abbas Rahimi, Frank K. Gürkaynak, Qiuting Huang, Luca Benini |
ISCAS | 1 |
| 2017 | Towards a Mobile Health Platform with Parallel Processing and Multi-sensor CapabilitiesabstractWe present ongoing work on a platform for mobile health and implantable telemetry devices with powerful point-of-contact processing capabilities based on our VivoSoC multi-sensor medical instrumentation SoC, a custom power management IC, and only a few additional components - allowing the realisation of sub-ccm devices. We detail the powerful yet efficient acquisition and parallel processing capabilities on the example of first applications, demonstrate system- and chip-level power management and address the application-layer considerations of a file system optimised for serial flash devices and job scheduling. Florian Glaser, Philipp Schönle, Pascale Meier, Jonathan Bosser, Noé Brun, Thomas Burger, Schekeb Fateh, Giovanni Rovere, Luca Benini, Qiuting Huang |
DSD | 1 |