© 2026 Plasma-PEPSC

List of Publications

IndexTitleAuthorsDownload
1Leveraging HPC Profiling & Tracing Tools to Understand the Performance of Particle-in-Cell Monte Carlo SimulationsWilliams, J. J., Tskhakaya, D., Costea, S., Peng, I. B., Garcia-Gasulla, M., and Markidis, S.PDF
2Optimizing BIT1, a Particle-in-Cell Monte Carlo Code, with OpenMP/OpenACC and GPU AccelerationWilliams, J. J., Liu, F., Tskhakaya, D., Costea, S., Podolnik, A., and Markidis, S.PDF
3Enabling High-Throughput Parallel I/O in Particle-in-Cell Monte Carlo Simulations with openPMD and Darshan I/O MonitoringWilliams, J. J., Medeiros, D., Costea, S., Tskhakaya, D., Poeschel, F., Widera, R., Huebl, A., Klasky, S., Podhorszki, N., Kos, L., Podolnik, A., Hromadka, J., Narwal, T., Steiniger, K., Bussmann, M., Laure, E., and Markidis S.PDF
4Understanding the Impact of openPMD on BIT1, a Particle-in-Cell Monte Carlo Code, through Instrumentation, Monitoring, and In-Situ AnalysisWilliams, J. J., Costea, S, Malony, A. D., Tskhakaya, S., Kos, L., Podolnik, A., Hromadka, J., Huck, K., Laure, E., Markidis, S.PDF
5Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on SupercomputersWilliams, J. J., Bhole, A., Kierans, D., Hoelzl, M., Holod, I., Tang, W., Tskhakaya, D., Costea, S., Kos, L., Podolnik, A. and Hromadka, J., Team, JOREK, Laure, E., and Markidis, S.PDF
6Accelerating Particle-in-Cell Monte Carlo Simulations with MPI, OpenMP/OpenACC and Asynchronous Multi-GPU ProgrammingWilliams, J. J., Liu, F., Trilaksono, J., Tskhakaya, D., Costea, S., Kos, L., Podolnik, A., Hromadka, J., Hegde, P., Garcia-Gasulla, M., Seitz, V., Jenko, F., Laure, E., and Markidis, S.PDF
7Integrating High Performance In-Memory Data Streaming and In-Situ Visualization in Hybrid MPI+OpenMP PIC MC Simulations Towards ExascaleWilliams, J. J., Costea, S., Medeiros, D., Trilaksono, J., Hegde, P., Tskhakaya, D., Kos, L., Podolnik, A., Hromadka, J., Huck, K. A., Malony, A. D., Jenko, F., Laure, E., Markidis, S.PDF
8Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing SystemsWilliams, J. J., Trilaksono, J., Costea, S., Ju, Y., Pennati, L., Ekelund, J., Tskhakaya, D., Kos, L., Podolnik, A., Hromadka, J., Malony, A. D., Shende, S., Dannert, T., Jenko, F., Laure, E., Markidis, S.PDF
9MPI Performance Analysis in Vlasiator: Unraveling Communication BottlenecksFaj, J., Williams, J.J., Peng, I.B., Ganse, U., Battarbee, M., Pfau-Kempf, Y., Kotipalo, L., Palmroth, M., and Markidis, S.PDF
10Integration of Modern HPC Performance Tools in Vlasiator for Exascale Analysis and OptimizationCoti, C., Pfau-Kempf, Y., Battarbee, M., Ganse, U., Shende, S., Huck, K., Rodriquez, J., Kotipalo, L., Faj, J., Williams, J.J., Peng, I., Malony, A. D., Markidis, S., and Palmroth M.PDF
11Characterizing the Performance of the GENE-X Code for Gyrokinetic Turbulence SimulationsTrilaksono, J., Williams, J. J., Ulbl, P., Dannert, T., Laure, E., Markidis, S., and Jenko, F.PDF
12A Hybrid Quantum-Classical Particle-in-Cell Method for Plasma SimulationsHegde, P. R., Marcandelli, P., He, Y., Pennati, L., Williams, J. J., Peng, I., & Markidis, S.PDF
13OpenACC and OpenMP-Accelerated Fortran/C++ Gyrokinetic Fusion Code GENE-X for Heterogeneous ArchitecturesTrilaksono, J., Ulbl, P., Williams, J. J., Pfeiler, C.M., Finkbeiner, M., Dannert, T., Laure, E., Markidis, S., Jenko, F.PDF
14Physics-Aware Compression of Plasma Distribution Functions with GPU-Accelerated Gaussian Mixture ModelsHu, A., Pennati, L., Peng, I., & Markidis, S. PDF
15A Parallel and Highly-Portable HPC Poisson Solver: Preconditioned Bi-CGSTAB with alpakaPennati, L., Andersson, M. I., Steiniger, K., Widera, R., Narwal, T., Bussmann, M., & Markidis, S. PDF
16Porting the grid-based 3D+ 3V hybrid-Vlasov kinetic plasma simulation Vlasiator to heterogeneous GPU architecturesBattarbee, M., Papadakis, K., Ganse, U., Hokkanen, J., Kotipalo, L., Pfau-Kempf, Y., Alho, M. and Palmroth, M.PDF
17Global evolution of flux transfer events along the magnetopause from the dayside to the far tailPfau-Kempf, Y., Papadakis, K., Alho, M., Battarbee, M., Cozzani, G., Pänkäläinen, L., Ganse, U., Kebede, F., Suni, J., Horaites, K., Grandin, M., and Palmroth M.PDF
18The Vlasiator 5.2 ionosphere – coupling a magnetospheric hybrid-Vlasov simulation with a height-integrated ionosphere modelGanse, U., Pfau-Kempf, Y., Zhou, H., Juusola, L., Workayehu, A., Kebede, F., Papadakis, K., Grandin, M., Alho, M., Battarbee, M., Dubart, M., Kotipalo, L., Lalagüe, A., Suni, J., Horaites, K., and Palmroth, M. PDF
19Physics-motivated cell-octree adaptive mesh refinement in the Vlasiator 5.3 global hybrid-Vlasov codeKotipalo, L., Battarbee, M., Pfau-Kempf, Y., and Palmroth, M.PDF
20Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace HopperSchieffer, G., Wahlgren, J., Ren, J., Faj, J., and Peng, I.PDF
21On the Rise of AMD Matrix Cores: Performance, Power Efficiency, and ProgrammabilitySchieffer, G., De Medeiros, D. A., Faj, J., Marathe, A., & Peng, I.PDF
22Understanding Data Movement in AMD Multi-GPU Systems with Infinity FabricSchieffer, G., Shi, R., Markidis, S., Herten, A., Faj, J., & Peng, I.PDF
23Integration of Modern HPC Performance Analysis in Vlasiator for Sustained ExascaleCoti, C., Malony, A. D., Shende, S., Huck, K., Rodriquez, J., Pfau-Kempf, Y., Battarbee, M., Ganse, U. and Palmroth, M.PDF
24Beyond the Buzz: Strategic Paths for Enabling Useful NISQ ApplicationsHegde, P.R., Kyriienko, O., Heimonen, H., Tolias, P., Netzer, G., Barkoutsos, P., Vinuesa, R., Peng, I. and Markidis, S.PDF
25Coalescing MPI communication in 6D Vlasov simulations: solving ghost domains in VlasiatorBattarbee, M., Ganse, U., Pfau-Kempf, Y., Alho, M., Papadakis, K. and Palmroth, M.PDF
26Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA GraphsEkelund, J., Markidis, S., & Peng, I.PDF
27Non-Blocking GPU-CPU Notifications to Enable More GPU-CPU ParallelismElis B., Pearce O., Boehme D., Burmark J., and Schulz M.PDF
28Quantum Computer Simulations at Warp Speed: Assessing the Impact of GPU Acceleration: A Case Study with IBM Qiskit Aer, Nvidia Thrust & cuQuantumFaj J, Peng I, Wahlgren J, and Markidis S.PDF
29Programming Quantum Neural Networks on NISQ Systems: An Overview of Technologies and MethodologiesMarkidis S.PDF
30Enabling Quantum Computer Simulations on AMD GPUs: a HIP Backend for Google’s qsimMarkidis S.PDF
31Dynamic Resource Management for In-Situ Techniques Using MPI-SessionsJu, Y., Huber, D., Perez A., Ulbl P., Markidis S., Schlatter P., Schulz M., Schreiber M., and Laure E.PDF
32A Performance Model of In-Situ TechniquesJu, Y., Nicolas, V., Perez, A., Gainaru, A., Suter, F., Markidis, S., Schlatter, P., Klasky, S., and Laure, E.PDF
33Hashinator: a portable hybrid hashmap designed for heterogeneous high performance computingPapadakis, K., Battarbee, M., Ganse, U., Pfau-Kempf, Y., and
Palmroth, M.		PDF
34Streaming Data in HPC Workflows Using ADIOSEisenhauer, G., Podhorszki, N., Gainaru A., Klasky, S., Davis, P.E., Parashar, M., Wolf, M., Suchtya. E, Fredj, E., Bolea, V., Pöschel, F., Steiniger, K., Bussmann, M., Pausch, R, and Chandrasekaran, S.PDF

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