< Back to previous page
Researcher
Marian Verhelst
- Disciplines:Nanotechnology, Sensors, biosensors and smart sensors, Other electrical and electronic engineering, Design theories and methods
Affiliations
- Electronic Circuits and Systems (ECS) (Division)
Member
From1 Aug 2020 → 30 Sep 2022 - ESAT - MICAS, Microelectronics and Sensors (Division)
Member
From1 Dec 2007 → 31 Jul 2020 - Department of Electrical Engineering (ESAT) (Department)
Member
From1 Oct 2003 → 30 Nov 2007
Projects
1 - 10 of 60
- Explore chiplet-based processors that can be easily integrated together / tiled in a heterogeneous wayFrom29 Apr 2024 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Bringing generative AI to edge devices through interoperable heterogeneous compute coresFrom5 Mar 2024 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Lifelong-Learning Electronic Systems: edge-devices that get smarter day-by-day [LifeLinES]From1 Jan 2024 → TodayFunding: BOF - Methusalem
- Digital in memory compute for low energy biomedical machine learning applicationsFrom23 Nov 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Scalable large array nanopore readouts for proteomics and next-generation sequencingFrom2 Oct 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Efficient scheduling and compilation of embedded multi-core AI platformsFrom1 Sep 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Efficient multi-core processor design for heterogeneous AI workloadsFrom7 Aug 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Outplaying the hardware lottery for embedded AIFrom1 Jun 2023 → TodayFunding: Horizon Europe - European Research Council (ERC)
- System-Technology Co-optimization for enablement of MRAM-based Machine LearningFrom25 May 2023 → 7 Mar 2024Funding: Own budget, for example: patrimony, inscription fees, gifts
- Design Automation and Exploration for Energy Efficient Machine Learning SoCs and ChipletsFrom31 Jan 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
Publications
21 - 30 of 231
- Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators(2023)
Authors: Arne Symons, Linyan Mei, Pouya Houshmand, Marian Verhelst
Pages: 355 - 357Number of pages: 3 - DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling(2023)
Authors: Linyan Mei, Arne Symons, Marian Verhelst
Pages: 570 - 583Number of pages: 14 - A 96-channel 40nm CMOS Potentiostat for Parallel Experiments on Microbial Electrochemical Systems(2023)
Authors: Peishuo Li, Marian Verhelst
- PATRONoC: Parallel AXI Transport Reducing Overhead for Networks-on-Chip targeting Multi-Accelerator DNN Platforms at the Edge(2023)
Authors: Marian Verhelst
Number of pages: 6 - Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference(2023)
Authors: Giuseppe Sarda, Marian Verhelst
Number of pages: 6 - Optimising GPGPU Execution Through Runtime Micro-Architecture Parameter Analysis(2023)
Authors: Giuseppe Sarda, Marian Verhelst
Pages: 226 - 228Number of pages: 3 - HTVM: Efficient Neural Network Deployment On Heterogeneous TinyML Platforms(2023)
Authors: Giuseppe Sarda, Marian Verhelst
Number of pages: 6 - PetaOps/W edge-AI μProcessors: Myth or reality?(2023)
Authors: Linyan Mei, Marian Verhelst
Number of pages: 6 - Hardware-Aware Mobile Building Block Evaluation for Computer Vision(2022)
Authors: Marian Verhelst
- GRAPHOPT: constrained-optimization-based parallelization of irregular graphs(2022)
Authors: Nimish Shirishbhai Shah, Wannes Meert, Marian Verhelst
Pages: 3321 - 3332
Patents
1 - 3 of 3