Cargando…
The BondMachine toolkit: Enabling Machine Learning on FPGA
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...
Autores principales: | , , , , , |
---|---|
Lenguaje: | eng |
Publicado: |
SISSA
2019
|
Materias: | |
Acceso en línea: | https://dx.doi.org/10.22323/1.351.0020 http://cds.cern.ch/record/2708682 |
Sumario: | 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. |
---|