N. Bellas et al., “Architectures for SLAM and Augmented Reality Computing”, International Conference on Field-Programmable Logic and Applications (FPL), 9 vol. Virtual Conference, 2021.
M. R. Gkeka, Patras, A., Antonopoulos, C. D. D., Lalis, S., and Bellas, N., “FPGA Architectures for Approximate Dense SLAM Computing”, 2021, 02 vol.
V. Vassiliadis et al., “A programming model and runtime system for significance-aware energy-efficient computing”, ACM 20th Symposium on Principles and Practice of Parallel Programming (PPoPP), 02 vol. San Francisco, CA, pp. 275-276, 2015, doi: 10.1145/2688500.2688546.
M. Spyrou et al., “Energy Minimization on Heterogeneous Systems through Approximate Computing”, International Conference on Parallel Computing (PARCO), 09 vol. Edinburgh, UK, pp. 741-752, 2015, doi: 10.3233/978-1-61499-621-7-741.
D. S. Nikolopoulos et al., “Energy Efficiency through Significance-Based Computing”, IEEE Computer, vol. 47, 07 vol., Art. no. 7, 2014, doi: 10.1109/MC.2014.182.
I. Parnassos et al., “A programming model and runtime system for approximation-aware heterogeneous computing”, International Symposium on Field Programmable Logic and Applications (FPL), 09 vol. Ghent, Belgium, pp. 1-4, 2017, doi: 10.23919/FPL.2017.8056774.
V. Vassiliadis et al., “Exploiting Significance of Computations for Energy-Constrained Approximate Computing”, International Journal of Parallel Programming (IJPP), vol. 44, 03 vol., Art. no. 5, 2016, doi: 10.1007/s10766-016-0409-6.
V. Vassiliadis et al., “Towards automatic significance analysis for approximate computing”, International Symposium on Code Generation and Optimization (CGO), 03 vol. Barcelona, Spain, pp. 182-193, 2016, doi: 10.1145/2854038.2854058.
V. Vassiliadis et al., “A significance-driven programming framework for energy-constrained approximate computing”, ACM International Conference on Computing Frontiers (CF), 05 vol. Ischia, Italy, pp. 1-9, 2015, doi: 10.1145/2742854.2742857.
P. K. Koutsovasilis, Kalogirou, C., Konstantas, C., Maroudas, E., Spyrou, M., and Antonopoulos, C. D. D., “AcHEe: Evaluating approximate computing and heterogeneity for energy efficiency”, Parallel Computing, vol. 73, 04 vol., 2018, doi: 10.1016/j.parco.2017.03.002.