GPAI - General Purpose AI Computing: Publications

GPAI - General Purpose AI Computing: Publications

Journal articles

J. Keller, S. Litzinger, and C. Kessler, "Integrating Energy-Optimizing Scheduling of Moldable Streaming Tasks with Design Space Exploration for Multiple Core Types on Configurable Platforms," Journal of Signal Processing Systems, vo. 94, pp. 849-864, 2022. https://doi.org/10.1007/s11265-022-01787-y

L. Lundberg and H. Grahn, "Research Trends, Enabling Technologies and Application Areas for Big Data," Algorithms, 15(8):280, August 2022. doi: https://doi.org/10.3390/a15080280

C. Åleskog, H. Grahn, and A. Borg, "Recent Developments in Low-Power AI Accelerators: A Survey," Algorithms, 15(11):419, November 2022. doi: https://doi.org/10.3390/a15110419

A. Ernstsson, D. Griebler, and C. Kessler, "Assessing Application Efficiency and Performance Portability in Single-Source Programming for Heterogeneous Parallel Systems," International Journal of Parallel Programming, Volume 51, pages 61–82, 2023. https://doi.org/10.1007/s10766-022-00746-1

S. Litzinger, J. Keller, and C. Kessler, "Packing Multiple Types of Cores for Energy-Optimized Heterogeneous Hardware-Software Co-Design of Moldable Streaming Computations," in IEEE Access, vol. 11, pp. 19301-19311, 2023. https://doi.org/10.1109/ACCESS.2023.3248283

Peer-reviewed Conference and Workshop papers

C. Kessler, J. Keller, and S. Litzinger, "Temperature-Aware Energy-Optimal Scheduling of Moldable Streaming Tasks onto 2D-Mesh-Based Many-Core CPUs with DVFS," Proc. 24th Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP 2021) in conjunction with IPDPS 2021, Portland, Oregon USA, 21 May 2021, Springer LNCS.