We present GraphTensor, a comprehensive open-source framework that suppo...
Supporting atomic durability of updates for persistent memories is typic...
This paper proposes TRAININGCXL that can efficiently process large-scale...
Graph neural networks (GNNs) process large-scale graphs consisting of a
...
Traditional graphics processing units (GPUs) suffer from the low memory
...
Large persistent memories such as NVDIMM have been perceived as a disrup...
We propose ZnG, a new GPU-SSD integrated architecture, which can maximiz...
Host-side page victimizations can easily overflow the SSD internal buffe...
Emerging storage systems with new flash exhibit ultra-low latency (ULL) ...
Large-scale systems with all-flash arrays have become increasingly commo...
In this work, we propose FUSE, a novel GPU cache system that integrates
...
SSDs become a major storage component in modern memory hierarchies, and ...
For modern flash-based SSDs, the performance overhead of internal data
m...
A modern GPU aims to simultaneously execute more warps for higher
Thread...
Energy efficiency and computing flexibility are some of the primary desi...
Large-scale systems with arrays of solid state disks (SSDs) have become
...
Block traces are widely used for system studies, model verifications, an...
Existing solid state drive (SSD) simulators unfortunately lack hardware
...
Resource utilization is one of the emerging problems in many-chip SSDs. ...
Storage-class memory (SCM) combines the benefits of a solid-state memory...