Spatial joins are among the most time-consuming queries in spatial data management
systems. In this paper, we propose SwiftSpatial, a specialized accelerator architecture …

Abstract The Apache Flink distributed computing system demonstrates significant
advantages in iterative computing. Establishing appropriate parallelism for operators is …

This paper presents a novel approach for accelerating the top-k heavy hitters query in data
streams using Field Programmable Gate Arrays (FPGAs). Current hardware acceleration …

The Compute Express Link (CXL) interconnect has provided the ability to integrate diverse
memory types into servers via byte-addressable SerDes links. Harnessing the full potential …

Retrieval-augmented language models (RALMs) present an evolving frontier in natural
language processing, combining the capabilities of conventional large language models …

Improving the performance and reducing the cost of cloud data systems is increasingly
challenging. Data processing units (DPUs) are a promising solution, but utilizing them for …

Sketch algorithms are crucial for data stream analysis, offering one-pass processing, sub-
linear storage, and accuracy-performance balance. FPGA-based sketch accelerator helps …

Serverless computing is extensively employed in distributed storage computing scenarios
owing to its dynamic responsiveness and on-demand allocation capabilities. Within …

The spatial join is one of the most expensive operations in modern spatial database
systems. Throughout the years a number of indices, join algorithms, and different …

Martin Kiefer Page 1 Accelerating Approximate Data Analysis with Parallel Processors 2.2.2023
Martin Kiefer PhD Defense Page 2 Approximate Data Analysis Trading accuracy for faster …