Understanding Energy Aspects of Processing-near-Memory for HPC Workloads
Interests in the concept of processing-near-memory (PNM) have been reignited with recent improvements of the 3D integration technology. In this work, we analyze the energy consumption characteristics of a system which comprises a conventional processor and a 3D memory stack with fully-programmable cores. We construct a high-level analytical energy model based on the underlying architecture and the technology with which each component is built. From the preliminary experiments with 11 HPC benchmarks from Mantevo benchmark suite, we observed that misses per kilo instructions (MPKI) of last-level cache (LLC) is one of the most important characteristics in determining the friendliness of the application to the PNM execution.
Summary. This paper presents some results of a case study about the characteristics of the interactions between pupils in groupworks, in the context of an innovative teaching experience of Physics at university level. Videorecordings were carried ou t during classes of the unit on Thermodynamics and some pupils from a focal group were interviewed. Analysis focused on group processes from the linguistic, social and cognitive perspectives. Results suggest that sharing cognitive processes by a group o f student, through reasoning and argumentation, may be an answer to the challenges of teaching practice at university level.