Optimization of Execution Time under Power Consumption Constraints in a Heterogeneous Parallel System with GPUs and CPUs. - Pawel Czarnul; Pawel Rosciszewski (ICDCN, 2014)

Simulation of parallel similarity measure computations for large data sets. - Pawel Czarnul; Pawel Rosciszewski; Mariusz R. Matuszek; Julian Szymanski (CYBCONF, 2015)

Modeling energy consumption of parallel applications. - Pawel Czarnul; Jaroslaw Kuchta; Pawel Rosciszewski; Jerzy Proficz (FedCSIS, 2016)

KernelHive: a new workflow-based framework for multilevel high performance computing using clusters and workstations with CPUs and GPUs. - Pawel Rosciszewski; Pawel Czarnul; Rafal Lewandowski; Marcel Schally-Kacprzak (Concurr. Comput. Pract. Exp., 2016)

Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training. - Pawel Rosciszewski (ICCS, 2017)

Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging. - Pawel Rosciszewski; Jakub Kaliski (HPCS, 2017)

From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition. - Pawel Rosciszewski (Comput. Sci., 2017)

MERPSYS: An environment for simulation of parallel application execution on large scale HPC systems. - Pawel Czarnul; Jaroslaw Kuchta; Mariusz R. Matuszek; Jerzy Proficz; Pawel Rosciszewski; Michal Wójcik; Julian Szymanski (Simul. Model. Pract. Theory, 2017)

Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption. - Pawel Rosciszewski (CoRR, 2018)

Auto-tuning methodology for configuration and application parameters of hybrid CPU + GPU parallel systems based on expert knowledge. - Pawel Czarnul; Pawel Rosciszewski (HPCS, 2019)

The impact of the AC922 Architecture on Performance of Deep Neural Network Training. - Pawel Rosciszewski; Michal Iwanski; Pawel Czarnul (HPCS, 2019)

Automated Classifier Development Process for Recognizing Book Pages from Video Frames. - Adam Brzeski; Jan Cychnerski; Karol Draszawka; Krystyna Dziubich; Tomasz Dziubich; Waldemar Korlub; Pawel Rosciszewski (ADBIS/TPDL/EDA Workshops, 2020)

Towards Scalable Simulation of Federated Learning. - Tomasz Kolodziej; Pawel Rosciszewski (ICONIP (5), 2021)

TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads. - Pawel Rosciszewski; Michal Martyniak; Filip Schodowski (J. Mach. Learn. Res., 2021)

Adaptation of AI-Accelerated CFD Simulations to the IPU Platform. - Pawel Rosciszewski; Adam Krzywaniak; Sergio Iserte; Krzysztof Rojek; Pawel Gepner (PPAM (2), 2022)

Optimizing throughput of Seq2Seq model training on the IPU platform for AI-accelerated CFD simulations. - Pawel Rosciszewski; Adam Krzywaniak; Sergio Iserte; Krzysztof Rojek; Pawel Gepner (Future Gener. Comput. Syst., 2023)