Data-intensive queries are common in business intelligence, data warehousing and
analytics applications. Typically, processing a query involves full inspection of large in …

Neural personalized recommendation models are used across a wide variety of datacenter
applications including search, social media, and entertainment. State-of-the-art models …

The cost of data movement in big-data systems motivates careful examination of near-data
processing (NDP) frameworks. The concept of NDP was actively researched in the 1990s …

Flash storage has become the mainstream destination for storage users. However, SSDs do
not always deliver the performance that users expect. The core culprit of flash performance …

Big data applications often incur large costs in I/O, data transfer and copying overhead,
especially when operating in cloud environments. Since most such computations are …

Compute express link (CXL) is the first open multi-protocol method to support cache
coherent interconnect for different processors, accelerators, and memory device types. Even …

Modern data center solid state drives (SSDs) integrate multiple general-purpose embedded
cores to manage flash translation layer, garbage collection, wear-leveling, and etc., to …

We present INSIDER, a full-stack redesigned storage system to help users fully utilize the
performance of emerging storage drives with moderate programming efforts. On the …

Solid State Drives (SSDs) were initially developed as faster storage devices intended to
replace conventional magnetic Hard Disk Drives (HDDs). However, high computational …

Graph neural networks (GNNs) can extract features by learning both the representation of
each objects (ie, graph nodes) and the relationship across different objects (ie, the edges …