With the sheer volume of data in today’s world, archive storage systems play a significant role in persisting the cold data. Due to stringent cost concerns, one popular design is to organize disks into groups and periodically switch them to be powered on ...

Modern solid-state drives (SSDs) continue to boost storage density and I/O bandwidth at the cost of flash-access I/O latency, especially for write, hence prevalently deploy a build-in buffer to absorb incoming writes. However, when the buffer is used up, ...

Emerging Zoned Namespace (ZNS) provides hosts with fine-grained, performance-predictable storage management. ZNS organizes the address space into zones composed of fixed-size, sequentially written, non-overwritable blocks, making it suitable for log-...

The CPU overhead of the LSM-tree becomes increasingly significant when high-speed storage devices are utilized. In this article, we propose SuccinctKV, a key-value store based on LSM-tree that is optimized to improve CPU efficiency in mixed workload ...

The NVMe Zoned Namespace (ZNS) is a high-performance interface for flash-based solid-state drives (SSDs), which divides the logical address space into fixed-size and sequential-write zones. Meanwhile, ZNS SSDs eliminate in-device garbage collection (GC) ...

Due to the limited GPU memory, the performance of large DNNs training is constrained by the unscalable batch size. Existing researches partially address the issue of GPU memory limit through tensor recomputation and swapping, but overlook the exploration ...

Today, real-time search over big microblogging data requires low indexing and query latency. Online services, therefore, prefer to host inverted indices in memory. Unfortunately, as datasets grow, indices grow proportionally, and with limited DRAM scaling,...

Workload consolidation is a widely used approach to enhance resource utilization in modern data centers. However, the concurrent execution of multiple jobs on a shared server introduces contention for essential shared resources such as CPU cores, Last ...

Disaggregated memory separates compute and memory resources into independent pools connected by RDMA (Remote Direct Memory Access) networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. ...

With the development of NAND flash memories’ bit density and stacking technologies, while storage capacity keeps increasing, the issue of reliability becomes increasingly prominent. Low-density parity check (LDPC) code, as a robust error-correcting code, ...

LSM-based key-value stores suffer from sub-optimal performance due to their slow and heavy background compactions. The compaction brings severe CPU and network overhead on high-speed disaggregated storage. This article further reveals that data-intensive ...

Persistent memory (PM) presents a unique opportunity for designing data management systems that offer improved performance, scalability, and instant restart capability. As a widely used data structure for managing data in such systems, B⁺-Tree must ...

Learned Index, which utilizes effective machine learning models to accelerate locating sorted data positions, has gained increasing attention in many big data scenarios. Using efficient learned models, the learned indexes build large nodes and flat ...

ZNS SSDs divide the storage space into sequential-write zones, reducing costs of DRAM utilization, garbage collection, and over-provisioning. The sequential-write feature of zones is well-suited for LSM-based databases, where random writes are organized ...

In recent years, benefiting from the increase in model size and complexity, deep learning has achieved tremendous success in computer vision (CV) and (NLP). Training deep learning models using accelerators such as GPUs often requires much iterative data ...

Erasure codes are widely deployed in modern storage systems, leading to frequent usage of their encoding/decoding operations. The encoding/decoding process for erasure codes is generally carried out using the parity-check matrix approach. However, this ...

Deep Neural Networks (DNNs) have achieved remarkable success in various real-world applications. However, running a Deep Neural Network (DNN) typically requires hundreds of megabytes of memory footprints, making it challenging to deploy on resource-...

The Zoned Namespace (ZNS) Solid State Drive (SSD) is a nascent form of storage device that offers novel prospects for the Log Structured Merge Tree (LSM-tree). ZNS exposes erase blocks in SSD as append-only zones, enabling the LSM-tree to gain awareness ...

GPU database systems are an effective solution to query optimization, particularly with compilation and data caching. They fall short, however, in end-to-end workloads, as existing compiler toolchains are too expensive for use with short-running queries. ...

Persistent memory (PM) provides large-scale non-volatile memory (NVM) with DRAM-comparable performance. The non-volatility and other unique characteristics of PM architecture bring new opportunities and challenges for the efficient storage system design. ...