Cache management is a critical aspect of computer architecture, encompassing techniques
such as cache replacement, bypassing, and prefetching. Existing research has often …

Reinforcement Learning (RL) is the process by which an agent learns optimal behavior
through interactions with experience datasets, all of which aim to maximize the reward …

Online Reinforcement Learning (RL) has been adopted as an effective mechanism in
various decision-making problems in microarchitecture. Its high adaptability and the ability to …

Resource disaggregation offers a cost effective solution to resource scaling, utilization, and
failure-handling in data centers by physically separating hardware devices in a server …

Fast and accurate climate simulations and weather predictions are critical for understanding
and preparing for the impact of climate change. Real-world climate and weather simulations …

Training machine learning (ML) algorithms is a computationally intensive process, which is
frequently memory-bound due to repeatedly accessing large training datasets. As a result …

GPU-based heterogeneous architectures are now commonly used in HPC clusters. Due to
their architectural simplicity specialized for data-level parallelism, GPUs can offer much …

Data classification storage has emerged as an effective strategy, harnessing the diverse
performance attributes of storage devices and orchestrating a harmonious equilibrium …

With the adoption of new storage technologies like NVMs, tiered storage has gained
popularity in large-scale, hyper-converged clusters. The storage back-end of hyper …

Abstract Hybrid Main Memory introduces emerging non-volatile memory technologies and
reduces the DRAM footprint to address the increasing capacity demands of modern …