The High Energy Physics (HEP) community is approaching the High-Luminosity LHC (HL-LHC) upgrade, where the instantaneous luminosity will increase by a factor of 10 relative to the LHC design. This will provide exciting physics opportunities but also unprecedented computing challenges for the CMS and ATLAS experiments. In this talk, I will cover two innovative R&D efforts designed to help reduce the computing requirements and maximize the discovery potential of the HL-LHC. The first initiative is the Compact Framework for Effective Analysis (Coffea), the first fully functioning HEP analysis framework based on the usage of Big Data technologies. The second project is the mkFit algorithm, a highly parallelized version of the traditional Kalman filter algorithm for charged particle tracking. Through the efficient use of modern CPU architectures, mkFit has achieved a factor of 6 speedup with respect to the nominal CMS algorithm, with comparable physics performance. Lessons learned and future opportunities and plans will be discussed.
https://cern.zoom.us/j/96700422910?pwd=Ri9EUzV1QVcwdVZzNmtOTWhjUk9Ndz09
Meeting ID: 967 0042 2910
Passcode: 078758
One tap mobile
+13126266799,,96700422910# US (Chicago)
+13462487799,,96700422910# US (Houston)
Dial by your location
+1 312 626 6799 US (Chicago)
+1 346 248 7799 US (Houston)
+1 646 558 8656 US (New York)
+1 669 900 9128 US (San Jose)
+1 253 215 8782 US (Tacoma)
+1 301 715 8592 US (Germantown)
Meeting ID: 967 0042 2910
Find your local number: https://cern.zoom.us/u/agq162jgb
Join by SIP
96700422910@188.184.89.188
Join by H.323
188.184.89.188
Meeting ID: 967 0042 2910
Passcode: 078758
Elizabeth Brost