Speaker
Jin Huang
(Brookhaven National Lab)
Description
Streaming Readout has been adopted as the paradigm of data acquisition (DAQ) at many major experiments at LHC, RHIC, and the future EIC. Distinct from the traditional triggered readout, streaming DAQs rely on modern digital data processing for large factors of data reduction, which opens unique opportunities for the application of AI/ML that is high throughput, low latency, energy efficient, and reliable. In this talk, we will discuss an array of AI/ML applications for Streaming Readout on the platforms of ASICs, FPGAs, and novel AI accelerators.
| speaker affiliation | Brookhaven National Lab |
|---|
Primary author
Jin Huang
(Brookhaven National Lab)
