Abstract: As data analytics grow in popularity, the increasing volume of data and complexity of jobs require users to wait longer to see results, hindering productivity and causing frustration. To address this, we developed an actor-based data processing engine optimized for pipelined execution, featuring a flexible interface for defining control messages. This enables users to seamlessly […]

Abstract: Emerging IoT and edge applications demand fast response times that cannot be achieved by faraway cloud datacenters. This motivates building edge-cloud systems where nodes on the edge can participate in the processing and storage of data. However, building an edge-cloud transaction processing system faces two main challenges: (1) Inefficient transaction execution due to low concurrency […]

Abstract:  We have entered a data-centric computing era, characterized by the coexistence of diverse parallel and specialized hardware accelerators along with general-purpose processors. In this ecosystem, minimizing data movement has become a critical priority for the design of both systems and applications. Over the years, the CPU-centric ecosystem has evolved into a one-size-fits-all environment, supporting a […]

Abstract In an era where data-driven decision-making shapes industries, governments, and everyday life, the ability to leverage data science has become an essential skill. Modern data science tools—encompassing data collection, analysis, and advanced techniques such as artificial intelligence (AI), machine learning (ML), and large language models (LLMs)—play a critical role across diverse fields. However, many […]