Hardware-Conscious Data Processing (ST 2025) - tele-TASK

PODCAST · education

Hardware-Conscious Data Processing (ST 2025) - tele-TASK

Hardware development continuously advances, with different technologies improving at different paces. While the number of transistors in a CPU package grows, the single-core performance stagnates due to physical limitations. These trends require changes in data processing to keep database management systems efficient. In this lecture, we will take a look at current computer architectures and accelerator technologies and how they can be used for efficient data processing. We will cover CPU and memory architecture, the storage hierarchy, modern memory and storage technologies, such as NVMe, fast interconnects, such as Infiniband, NVLink, and CXL, and accelerators, such as GPUs and FPGAs. The course has a significant practical part, where the students learn to implement data structures and algorithms tailored to hardware-conscious data processing.

No episodes available yet.

Type above to search every episode's transcript for a word or phrase. Matches are scoped to this podcast.

Searching…

We're indexing this podcast's transcripts for the first time — this can take a minute or two. We'll show results as soon as they're ready.

No matches for "" in this podcast's transcripts.

Showing of matches

No topics indexed yet for this podcast.

Loading reviews...

ABOUT THIS SHOW

Hardware development continuously advances, with different technologies improving at different paces. While the number of transistors in a CPU package grows, the single-core performance stagnates due to physical limitations. These trends require changes in data processing to keep database management systems efficient. In this lecture, we will take a look at current computer architectures and accelerator technologies and how they can be used for efficient data processing. We will cover CPU and memory architecture, the storage hierarchy, modern memory and storage technologies, such as NVMe, fast interconnects, such as Infiniband, NVLink, and CXL, and accelerators, such as GPUs and FPGAs. The course has a significant practical part, where the students learn to implement data structures and algorithms tailored to hardware-conscious data processing.

HOSTED BY

Prof. Dr. Tilmann Rabl

Produced by tele-TASK

CATEGORIES

URL copied to clipboard!