Hardware development continuously advances, with different technologies improving at different pace. While the amount of transistors in a CPU package are growing, the single core performance is stagnating 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 technolgoies, such as NVM and NVMe; fast interconnects, such as Infiniband, RDMA, and NVLink; 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 concious data processing.
Hardware-Conscious Data Processing (ST 2022) - tele-TASK
Claim This Podcastby Prof. Dr. Tilmann Rabl
Podcast Overview
Hardware development continuously advances, with different technologies improving at different pace. While the amount of transistors in a CPU package are growing, the single core performance is stagnating 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 technolgoies, such as NVM and NVMe; fast interconnects, such as Infiniband, RDMA, and NVLink; 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 concious data processing.
Language
🇺🇲
Publishing Since
4/21/2022
1 verified contact email on file for Hardware-Conscious Data Processing (ST 2022) - tele-TASK
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
July 26, 2022
Query Compilation for Modern, Heterogenous Processors
July 20, 2022
Efficient Answering of Historical What-if Queries
July 19, 2022
Field Programmable Gate Arrays
19 total episodes available
Deep-dive analytics for Hardware-Conscious Data Processing (ST 2022) - tele-TASK
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is Hardware-Conscious Data Processing (ST 2022) - tele-TASK?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Information about guest appearances is not available.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.