A Hardware Co-design Workflow for Scientific Instruments at the Edge
Kazutomo Yoshii, Rajesh Sankaran, Sebastian Strempfer, Maksim, Levental, Mike Hammer, Antonino Miceli

TL;DR
This paper proposes a hardware co-design workflow using open-source tools to develop reusable, specialized streaming hardware components for scientific instruments at the edge, aiming to reduce data bottlenecks and improve performance.
Contribution
It introduces a novel design workflow for creating customizable, reusable hardware libraries for edge scientific instruments, leveraging Chisel and open-source hardware ecosystems.
Findings
Development of a hardware co-design workflow for edge instruments
Creation of reusable hardware libraries for streaming data
Potential to enhance data processing efficiency at the edge
Abstract
As spatial and temporal resolutions of scientific instruments improve, the explosion in the volume of data produced is becoming a key challenge. It can be a critical bottleneck for integration between scientific instruments at the edge and high-performance computers/emerging accelerators. Placing data compression or reduction logic close to the data source is a possible approach to solve the bottleneck. However, the realization of such a solution requires the development of custom ASIC designs, which is still challenging in practice and tends to produce one-off implementations unusable beyond the initial intended scope. Therefore, as a feasibility study, we have been investigating a design workflow that allows us to explore algorithmically complex hardware designs and develop reusable hardware libraries for the needs of scientific instruments at the edge. Our vision is to cultivate our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDistributed and Parallel Computing Systems · Scientific Computing and Data Management · Advanced Data Storage Technologies
