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ORCIDStylianos I. Venieris
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Books and Theses
- 2019
[b1]Stylianos I. Venieris:
Automated methodologies for mapping convolutional neural networks on reconfigurable hardware. Imperial College London, UK, 2019
Journal Articles
- 2024
- [j12]Stefanos Laskaridis
, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane:
The Future of Consumer Edge-AI Computing. IEEE Pervasive Comput. 23(3): 21-30 (2024) - [j11]Ioannis Panopoulos, Stylianos I. Venieris, Iakovos S. Venieris:
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads. ACM Trans. Embed. Comput. Syst. 23(4): 60:1-60:32 (2024) - [j10]Stylianos I. Venieris, Mário Almeida, Royson Lee, Nicholas D. Lane:
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution. IEEE Trans. Mob. Comput. 23(3): 2367-2381 (2024) - 2023
- [j9]Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane:
Multiple-Deep Neural Network Accelerators for Next-Generation Artificial Intelligence Systems. Computer 56(3): 70-79 (2023) - [j8]Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane:
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation. ACM Trans. Design Autom. Electr. Syst. 28(6): 92:1-92:31 (2023) - 2022
- [j7]Royson Lee, Stylianos I. Venieris, Nicholas D. Lane:
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions. ACM Comput. Surv. 54(8): 169:1-169:30 (2022) - [j6]Bo Han, Jiasi Chen, Tian Guo, Sung-Ju Lee, Viswanathan Swaminathan, Stylianos I. Venieris:
Guest Editorial: Bridging the Gap Between Industry and Academia for Networking Research. IEEE Netw. 36(1): 8-9 (2022) - [j5]Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane:
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. ACM Trans. Embed. Comput. Syst. 21(6): 71:1-71:24 (2022) - 2020
- [j4]Alexandros Kouris, Stylianos I. Venieris, Michail Rizakis, Christos-Savvas Bouganis:
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars. IEEE Consumer Electron. Mag. 9(4): 11-26 (2020) - [j3]Sourav Bhattacharya, Dionysis Manousakas, Alberto Gil C. P. Ramos, Stylianos I. Venieris, Nicholas D. Lane, Cecilia Mascolo:
Countering Acoustic Adversarial Attacks in Microphone-equipped Smart Home Devices. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(2): 73:1-73:24 (2020) - 2019
- [j2]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs. IEEE Trans. Neural Networks Learn. Syst. 30(2): 326-342 (2019) - 2018
- [j1]Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions. ACM Comput. Surv. 51(3): 56:1-56:39 (2018)
Conference and Workshop Papers
- 2024
- [c33]Young D. Kwon, Rui Li, Stylianos I. Venieris, Jagmohan Chauhan, Nicholas Donald Lane, Cecilia Mascolo:
TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge. ICML 2024 - [c32]Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. WACV 2024: 1485-1494 - 2023
- [c31]Ioannis Panopoulos, Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris:
Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devices. ISCC 2023: 1-4 - [c30]Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris:
MultiTASC: A Multi-Tenancy-Aware Scheduler for Cascaded DNN Inference at the Consumer Edge. ISCC 2023: 411-416 - [c29]Hongxiang Fan, Stylianos I. Venieris, Alexandros Kouris, Nicholas D. Lane:
Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads. MICRO 2023: 353-366 - [c28]Young D. Kwon, Jagmohan Chauhan, Hong Jia, Stylianos I. Venieris, Cecilia Mascolo:
LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms. SenSys 2023: 138-151 - 2022
- [c27]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Multi-Exit Semantic Segmentation Networks. ECCV (21) 2022: 330-349 - [c26]Hongxiang Fan, Thomas Chau, Stylianos I. Venieris, Royson Lee, Alexandros Kouris, Wayne Luk, Nicholas D. Lane, Mohamed S. Abdelfattah:
Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design. MICRO 2022: 599-615 - [c25]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Adaptable mobile vision systems through multi-exit neural networks. MobiSys 2022: 575-576 - 2021
- [c24]Stylianos I. Venieris, Ioannis Panopoulos, Ilias Leontiadis, Iakovos S. Venieris:
How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures. ASAP 2021: 93-100 - [c23]Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane:
unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation. FCCM 2021: 165-175 - [c22]Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. NeurIPS 2021: 12876-12889 - [c21]Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris:
OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices. SMARTCOMP 2021: 1-8 - [c20]Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane:
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. HotMobile 2021: 15-21 - 2020
- [c19]Royson Lee, Stylianos I. Venieris, Nicholas D. Lane:
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions. DistributedML@CoNEXT 2020: 34-41 - [c18]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
A Throughput-Latency Co-Optimised Cascade of Convolutional Neural Network Classifiers. DATE 2020: 1656-1661 - [c17]Royson Lee, Lukasz Dudziak, Mohamed S. Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane:
Journey Towards Tiny Perceptual Super-Resolution. ECCV (26) 2020: 85-102 - [c16]Diederik Adriaan Vink, Aditya Rajagopal, Stylianos I. Venieris, Christos-Savvas Bouganis:
Caffe Barista: Brewing Caffe with FPGAs in the Training Loop. FPL 2020: 317-322 - [c15]Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane:
HAPI: Hardware-Aware Progressive Inference. ICCAD 2020: 91:1-91:9 - [c14]Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis:
Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs. ICML 2020: 7943-7952 - [c13]Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane:
SPINN: synergistic progressive inference of neural networks over device and cloud. MobiCom 2020: 37:1-37:15 - 2019
- [c12]Alexander Montgomerie-Corcoran, Stylianos I. Venieris, Christos-Savvas Bouganis:
Power-Aware FPGA Mapping of Convolutional Neural Networks. FPT 2019: 327-330 - [c11]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
Towards Efficient On-Board Deployment of DNNs on Intelligent Autonomous Systems. ISVLSI 2019: 568-573 - [c10]Royson Lee, Stylianos I. Venieris, Lukasz Dudziak, Sourav Bhattacharya, Nicholas D. Lane:
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. MobiCom 2019: 54:1-54:16 - [c9]Royson Lee, Stylianos I. Venieris, Lukasz Dudziak, Sourav Bhattacharya, Nicholas D. Lane:
Poster: MobiSR - Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. MobiCom 2019: 90:1-90:3 - 2018
- [c8]Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Approximate FPGA-Based LSTMs Under Computation Time Constraints. ARC 2018: 3-15 - [c7]Christos Kyrkou, George Plastiras, Theocharis Theocharides, Stylianos I. Venieris, Christos-Savvas Bouganis:
DroNet: Efficient convolutional neural network detector for real-time UAV applications. DATE 2018: 967-972 - [c6]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
Cascade^CNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks. FPL 2018: 155-162 - [c5]Stylianos I. Venieris, Christos-Savvas Bouganis:
f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs. FPL 2018: 381-388 - 2017
- [c4]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: Automated Mapping of Convolutional Neural Networks on FPGAs (Abstract Only). FPGA 2017: 291-292 - [c3]Stylianos I. Venieris, Christos-Savvas Bouganis:
Latency-driven design for FPGA-based convolutional neural networks. FPL 2017: 1-8 - 2016
- [c2]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: A Framework for Mapping Convolutional Neural Networks on FPGAs. FCCM 2016: 40-47 - 2015
- [c1]Stylianos I. Venieris, Grigorios Mingas, Christos-Savvas Bouganis:
Towards heterogeneous solvers for large-scale linear systems. FPL 2015: 1-8
Informal and Other Publications
- 2024
- [i39]Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan:
Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference. CoRR abs/2405.18628 (2024) - [i38]Ioannis Panopoulos, Stylianos I. Venieris, Iakovos S. Venieris:
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads. CoRR abs/2409.01089 (2024) - 2023
- [i37]Ioannis Panopoulos, Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris:
Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devices. CoRR abs/2306.11426 (2023) - [i36]Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris:
MultiTASC: A Multi-Tenancy-Aware Scheduler for Cascaded DNN Inference at the Consumer Edge. CoRR abs/2306.12830 (2023) - [i35]Young D. Kwon, Rui Li, Stylianos I. Venieris, Jagmohan Chauhan, Nicholas D. Lane, Cecilia Mascolo:
TinyTrain: Deep Neural Network Training at the Extreme Edge. CoRR abs/2307.09988 (2023) - [i34]Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane:
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation. CoRR abs/2307.13412 (2023) - [i33]Hongxiang Fan, Stylianos I. Venieris, Alexandros Kouris, Nicholas D. Lane:
Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads. CoRR abs/2310.11096 (2023) - [i32]Young D. Kwon, Jagmohan Chauhan, Hong Jia, Stylianos I. Venieris, Cecilia Mascolo:
LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms. CoRR abs/2311.11420 (2023) - 2022
- [i31]Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane:
Multi-DNN Accelerators for Next-Generation AI Systems. CoRR abs/2205.09376 (2022) - [i30]Hongxiang Fan, Thomas Chun-Pong Chau, Stylianos I. Venieris, Royson Lee, Alexandros Kouris, Wayne Luk, Nicholas D. Lane, Mohamed S. Abdelfattah:
Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design. CoRR abs/2209.09570 (2022) - [i29]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs. CoRR abs/2209.13443 (2022) - [i28]Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane:
The Future of Consumer Edge-AI Computing. CoRR abs/2210.10514 (2022) - [i27]Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. CoRR abs/2212.07886 (2022) - [i26]Stylianos I. Venieris, Mário Almeida, Royson Lee, Nicholas D. Lane:
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution. CoRR abs/2212.09501 (2022) - 2021
- [i25]Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane:
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. CoRR abs/2102.01393 (2021) - [i24]Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. CoRR abs/2102.13451 (2021) - [i23]Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane:
unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation. CoRR abs/2103.05600 (2021) - [i22]Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane:
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. CoRR abs/2104.09949 (2021) - [i21]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Multi-Exit Semantic Segmentation Networks. CoRR abs/2106.03527 (2021) - [i20]Royson Lee, Stylianos I. Venieris, Nicholas D. Lane:
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions. CoRR abs/2106.03727 (2021) - [i19]Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris:
OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices. CoRR abs/2106.04723 (2021) - [i18]Stylianos I. Venieris, Ioannis Panopoulos, Ilias Leontiadis, Iakovos S. Venieris:
How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures. CoRR abs/2106.15021 (2021) - 2020
- [i17]Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis:
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs. CoRR abs/2006.09049 (2020) - [i16]Diederik Adriaan Vink, Aditya Rajagopal, Stylianos I. Venieris, Christos-Savvas Bouganis:
Caffe Barista: Brewing Caffe with FPGAs in the Training Loop. CoRR abs/2006.13829 (2020) - [i15]Royson Lee, Lukasz Dudziak, Mohamed S. Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane:
Journey Towards Tiny Perceptual Super-Resolution. CoRR abs/2007.04356 (2020) - [i14]Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane:
HAPI: Hardware-Aware Progressive Inference. CoRR abs/2008.03997 (2020) - [i13]Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane:
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud. CoRR abs/2008.06402 (2020) - [i12]Royson Lee, Stylianos I. Venieris, Nicholas D. Lane:
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions. CoRR abs/2010.05838 (2020) - 2019
- [i11]Alexandros Kouris, Stylianos I. Venieris, Michail Rizakis, Christos-Savvas Bouganis:
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars. CoRR abs/1905.00689 (2019) - [i10]Mário Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices. CoRR abs/1905.07346 (2019) - [i9]Royson Lee, Stylianos I. Venieris, Lukasz Dudziak, Sourav Bhattacharya, Nicholas D. Lane:
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. CoRR abs/1908.07985 (2019) - 2018
- [i8]Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Approximate FPGA-based LSTMs under Computation Time Constraints. CoRR abs/1801.02190 (2018) - [i7]Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions. CoRR abs/1803.05900 (2018) - [i6]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
CascadeCNN: Pushing the performance limits of quantisation. CoRR abs/1805.08743 (2018) - [i5]Stylianos I. Venieris, Christos-Savvas Bouganis:
f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs. CoRR abs/1805.10174 (2018) - [i4]Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Deploying Deep Neural Networks in the Embedded Space. CoRR abs/1806.08616 (2018) - [i3]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks. CoRR abs/1807.05053 (2018) - [i2]Christos Kyrkou, George Plastiras, Stylianos I. Venieris, Theocharis Theocharides, Christos-Savvas Bouganis:
DroNet: Efficient convolutional neural network detector for real-time UAV applications. CoRR abs/1807.06789 (2018) - 2017
- [i1]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs. CoRR abs/1711.08740 (2017)
Coauthor Index
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