Dynamic memory access monitoring based on tagged memory. - Mikhail A. Gorelov; Lev Mukhanov (PACT, 2013)

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling. - Lev Mukhanov; Dimitrios S. Nikolopoulos; Bronis R. de Supinski (PACT, 2015)

Power Capping: What Works, What Does Not. - Pavlos Petoumenos; Lev Mukhanov; Zheng Wang 001; Hugh Leather; Dimitrios S. Nikolopoulos (ICPADS, 2015)

ALEA: A Fine-Grained Energy Profiling Tool. - Lev Mukhanov; Pavlos Petoumenos; Zheng Wang 001; Konstantinos Parasyris; Dimitrios S. Nikolopoulos; Bronis R. de Supinski; Hugh Leather (ACM Trans. Archit. Code Optim., 2017)

An energy-efficient and error-resilient server ecosystem exceeding conservative scaling limits. - Georgios Karakonstantis; Konstantinos Tovletoglou; Lev Mukhanov; Hans Vandierendonck; Dimitrios S. Nikolopoulos; Peter Lawthers; Panos K. Koutsovasilis; Manolis Maroudas; Christos D. Antonopoulos; Christos Kalogirou; Nikolaos Bellas; Spyros Lalis; et al. (DATE, 2018)

Measuring and Exploiting Guardbands of Server-Grade ARMv8 CPU Cores and DRAMs. - Konstantinos Tovletoglou; Lev Mukhanov; Georgios Karakonstantis; Athanasios Chatzidimitriou; George Papadimitriou 001; Manolis Kaliorakis; Dimitris Gizopoulos; Zacharias Hadjilambrou; Yiannakis Sazeides; Alejandro Lampropulos; Shidhartha Das; Phong Vo (DSN Workshops, 2018)

DRAM Characterization under Relaxed Refresh Period Considering System Level Effects within a Commodity Server. - Lev Mukhanov; Konstantinos Tovletoglou; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (IOLTS, 2018)

Minimization of Timing Failures in Pipelined Designs via Path Shaping and Operand Truncation. - Ioannis Tsiokanos; Lev Mukhanov; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (IOLTS, 2018)

Variation-Aware Pipelined Cores through Path Shaping and Dynamic Cycle Adjustment: Case Study on a Floating-Point Unit. - Ioannis Tsiokanos; Lev Mukhanov; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (ISLPED, 2018)

Characterization of HPC workloads on an ARMv8 based server under relaxed DRAM refresh and thermal stress. - Lev Mukhanov; Konstantinos Tovletoglou; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (SAMOS, 2018)

Low-Power Variation-Aware Cores based on Dynamic Data-Dependent Bitwidth Truncation. - Ioannis Tsiokanos; Lev Mukhanov; Georgios Karakonstantis (DATE, 2019)

Workload-Aware DRAM Error Prediction using Machine Learning. - Lev Mukhanov; Konstantinos Tovletoglou; Hans Vandierendonck; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (IISWC, 2019)

Shimmer: Implementing a Heterogeneous-Reliability DRAM Framework on a Commodity Server. - Konstantinos Tovletoglou; Lev Mukhanov; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (IEEE Comput. Archit. Lett., 2019)

HaRMony: Heterogeneous-Reliability Memory and QoS-Aware Energy Management on Virtualized Servers. - Konstantinos Tovletoglou; Lev Mukhanov; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (ASPLOS, 2020)

Increasing the Profit of Cloud Providers through DRAM Operation at Reduced Margins. - Christos Kalogirou; Christos D. Antonopoulos; Nikolaos Bellas; Spyros Lalis; Lev Mukhanov; Georgios Karakonstantis (CCGRID, 2020)

DEFCON: Generating and Detecting Failure-prone Instruction Sequences via Stochastic Search. - Ioannis Tsiokanos; Lev Mukhanov; Giorgis Georgakoudis; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (DATE, 2020)

DStress: Automatic Synthesis of DRAM Reliability Stress Viruses using Genetic Algorithms. - Lev Mukhanov; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (MICRO, 2020)

Leveraging Transprecision Computing for Machine Vision Applications at the Edge. - Umar Ibrahim Minhas; Lev Mukhanov; Georgios Karakonstantis; Hans Vandierendonck; Roger F. Woods (SiPS, 2021)

A case study on profiling of an EEG-based brain decoding interface on Cloud and Edge servers. - Alexandra Samsonova; Barry J. Devereux; Georgios Karakonstantis; Lev Mukhanov (SmartCloud, 2021)

Resource-Efficient Deep Learning: A Survey on Model-, Arithmetic-, and Implementation-Level Techniques. - JunKyu Lee; Lev Mukhanov; Amir Sabbagh Molahosseini; Umar Ibrahim Minhas; Yang Hua 001; Jesús Martínez del Rincón; Kiril Dichev; Cheol-Ho Hong; Hans Vandierendonck (CoRR, 2021)

Revealing DRAM Operating GuardBands Through Workload-Aware Error Predictive Modeling. - Lev Mukhanov; Konstantinos Tovletoglou; Hans Vandierendonck; Dimitrios S. Nikolopoulos; Georgios Karakonstantis (IEEE Trans. Computers, 2021)

Instruction-aware Learning-based Timing Error Models through Significance-driven Approximations. - Styliani Tompazi; Ioannis Tsiokanos; Jesús Martínez del Rincón; Lev Mukhanov; Georgios Karakonstantis (ICCD, 2022)

On the Evaluation of the Total-Cost-of-Ownership Trade-Offs in Edge vs Cloud Deployments: A Wireless-Denial-of-Service Case Study. - Panagiota Nikolaou; Yiannakis Sazeides; Alejandro Lampropulos; Denis Guilhot; Andrea Bartoli; George Papadimitriou 001; Athanasios Chatzidimitriou; Dimitris Gizopoulos; Konstantinos Tovletoglou; Lev Mukhanov; Georgios Karakonstantis (IEEE Trans. Sustain. Comput., 2022)

Increased Leverage of Transprecision Computing for Machine Vision Applications at the Edge. - Umar Ibrahim Minhas; JunKyu Lee; Lev Mukhanov; Georgios Karakonstantis; Hans Vandierendonck; Roger F. Woods (J. Signal Process. Syst., 2022)

A case study on latency, bandwidth and energy efficiency of mobile 5G and YouTube Edge service in London. Why the 5G ecosystem and energy efficiency matter? - Peixuan Song; JunKyu Lee; Lev Mukhanov (CoRR, 2023)

Resource-Efficient Convolutional Networks: A Survey on Model-, Arithmetic-, and Implementation-Level Techniques. - JunKyu Lee; Lev Mukhanov; Amir Sabbagh Molahosseini; Umar Ibrahim Minhas; Yang Hua 001; Jesús Martínez del Rincón; Kiril Dichev; Cheol-Ho Hong; Hans Vandierendonck (ACM Comput. Surv., 2023)

ARETE: Accurate Error Assessment via Machine Learning-Guided Dynamic-Timing Analysis. - Ioannis Tsiokanos; Styliani Tompazi; Giorgis Georgakoudis; Lev Mukhanov; Georgios Karakonstantis (IEEE Trans. Computers, 2023)

Do 5G Networks Achieve The Proclaimed Promises? An Empirical Study Using YouTube Edge Service. - Peixuan Song; JunKyu Lee; Ahmed M. Abdelmoniem; Lev Mukhanov (EDGE, 2024)

Triangel: A High-Performance, Accurate, Timely On-Chip Temporal Prefetcher. - Sam Ainsworth; Lev Mukhanov (ISCA, 2024)

Towards LLM-based optimization compilers. Can LLMs learn how to apply a single peephole optimization? Reasoning is all LLMs need! - Xiangxin Fang; Lev Mukhanov (CoRR, 2024)

A Deep Technical Review of nZDC Fault Tolerance. - Minli Liao; Sam Ainsworth; Lev Mukhanov; Timothy M. Jones 001 (CC, 2025)

Parallaft: Runtime-Based CPU Fault Tolerance via Heterogeneous Parallelism. - Boyue Zhang; Sam Ainsworth; Lev Mukhanov; Timothy M. Jones 001 (CGO, 2025)

ParaVerser: Harnessing Heterogeneous Parallelism for Affordable Fault Detection in Data Centers. - Minli Julie Liao; Sam Ainsworth; Lev Mukhanov; Adrián Barredo; Markos Kynigos; Timothy M. Jones 001 (DSN, 2025)

Unlocking the power of 4G/5G mobile networks: An empirical dive into quality and energy efficiency in YouTube Edge services. - Peixuan Song; JunKyu Lee; Ahmed M. Abdelmoniem; Lev Mukhanov (Comput. Networks, 2025)