PoS - Proceedings of Science
Volume 351 - International Symposium on Grids & Clouds 2019 (ISGC2019) - Supercomputing, High Throughput Computing, Accelerator Technologies, and their Integration
The BondMachine toolkit: Enabling Machine Learning on FPGA
M. Mariotti,* L. Storchi, D. Spiga, D. Salomoni, T. Boccali, D. Bonacorsi
*corresponding author
Full text: pdf
Published on: November 21, 2019
Abstract
The BondMachine (BM) is an innovative prototype software ecosystem aimed at creating facilities where both hardware and software are co-designed, guaranteeing a full exploitation of fabric capabilities (both in terms of concurrency and heterogeneity) with the smallest possible power dissipation.
In the present paper we will provide a technical overview of the key aspects of the BondMachine toolkit, highlighting the advancements brought about by the porting of Go code in hardware. We will then show a cloud-based BM as a Service deployment. Finally, we will focus on TensorFlow, and in this context we will show how we plan to benchmark
the system with a ML tracking reconstruction from pp collision at the LHC.
DOI: https://doi.org/10.22323/1.351.0020
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.