Cost modelling for optimal data placement in heterogeneous main memory

R Lasch, T Legler, N May, B Scheirle… - Proceedings of the VLDB …, 2022 - dl.acm.org
The cost of DRAM contributes significantly to the operating costs of in-memory database
management systems (IMDBMS). Persistent memory (PMEM) is an alternative type of byte …

Accelerating Lattice QCD Simulations using GPUs

T Matthaei - arxiv preprint arxiv:2407.00041, 2024 - arxiv.org
Solving discretized versions of the Dirac equation represents a large share of execution time
in lattice Quantum Chromodynamics (QCD) simulations. Many high-performance computing …

In-DRAM cache management for low latency and low power 3D-stacked DRAMs

HH Shin, EY Chung - Micromachines, 2019 - mdpi.com
Recently, 3D-stacked dynamic random access memory (DRAM) has become a promising
solution for ultra-high capacity and high-bandwidth memory implementations. However, it …

Using Micro-Processor Vector Instructions to Optimize Unsupervised Machine Learning K-Means Algorithm

J Somarribas, A Loteanu - 2020 IEEE 11th Latin American …, 2020 - ieeexplore.ieee.org
The K-Means clustering algorithm is a widely used unsupervised learning technique for data
analysis that is still relevant decades after it was originally published. The algorithm is …