{SpanDB}: A fast,{Cost-Effective}{LSM-tree} based {KV} store on hybrid storage
Key-Value (KV) stores support many crucial applications and services. They perform fast in-
memory processing, but are still often limited by I/O performance. The recent emergence of …
memory processing, but are still often limited by I/O performance. The recent emergence of …
ZNS+: Advanced zoned namespace interface for supporting in-storage zone compaction
The NVMe zoned namespace (ZNS) is emerging as a new storage interface, where the
logical address space is divided into fixed-sized zones, and each zone must be written …
logical address space is divided into fixed-sized zones, and each zone must be written …
Hello bytes, bye blocks: Pcie storage meets compute express link for memory expansion (cxl-ssd)
M Jung - Proceedings of the 14th ACM Workshop on Hot Topics …, 2022 - dl.acm.org
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 …
coherent interconnect for different processors, accelerators, and memory device types. Even …
SSD-based workload characteristics and their performance implications
Storage systems are designed and optimized relying on wisdom derived from analysis
studies of file-system and block-level workloads. However, while SSDs are becoming a …
studies of file-system and block-level workloads. However, while SSDs are becoming a …
Don't be a blockhead: zoned namespaces make work on conventional SSDs obsolete
Research on flash devices almost exclusively focuses on conventional SSDs, which expose
a block interface. Industry, however, has standardized and is adopting Zoned Namespaces …
a block interface. Industry, however, has standardized and is adopting Zoned Namespaces …
{Hardware/Software}{Co-Programmable} framework for computational {SSDs} to accelerate deep learning service on {Large-Scale} graphs
Graph neural networks (GNNs) process large-scale graphs consisting of a hundred billion
edges. In contrast to traditional deep learning, unique behaviors of the emerging GNNs are …
edges. In contrast to traditional deep learning, unique behaviors of the emerging GNNs are …
Rearchitecting the {TCP} Stack for {I/O-Offloaded} Content Delivery
The recent advancement of high-bandwidth I/O devices enables scalable delivery of online
content. Unfortunately, the traditional programming model for content servers has a tight …
content. Unfortunately, the traditional programming model for content servers has a tight …
Behemoth: a flash-centric training accelerator for extreme-scale {DNNs}
The explosive expansion of Deep Neural Networks (DNN) model size expedites the need for
larger memory capacity. This movement is particularly true for models in natural language …
larger memory capacity. This movement is particularly true for models in natural language …
{ScalaAFA}: Constructing {User-Space}{All-Flash} Array Engine with Holistic Designs
All-flash array (AFA) is a popular approach to aggregate the capacity of multiple solid-state
drives (SSDs) while guaranteeing fault tolerance. Unfortunately, existing AFA engines inflict …
drives (SSDs) while guaranteeing fault tolerance. Unfortunately, existing AFA engines inflict …
Write dependency disentanglement with {HORAE}
Storage systems rely on write dependency to achieve atomicity and consistency. However,
enforcing write dependency comes at the expense of performance; it concatenates multiple …
enforcing write dependency comes at the expense of performance; it concatenates multiple …