Travelled to:1 × France
1 × Greece
2 × Germany
2 × USA
Collaborated with:R.Leupers S.Ertel A.Goens G.Ascheid N.A.Rink L.Schütze J.Adam W.Sheng A.Susungi A.Cohen C.Tadonki A.Tretter A.Brauckmann J.Ceng H.Meyr L.G.Murillo S.Wawroschek R.Velasquez A.Stulova I.Huismann J.Stiller J.Fröhlich H.Scharwächter T.Isshiki H.Kunieda L.Thiele L.Schor B.H.H.Juurlink M.A.Mesa A.Pohl R.Jessenberger V.Reyes
Talks about:composit (3) applic (3) map (3) parallel (2) program (2) tensor (2) effici (2) compil (2) optim (2) mpsoc (2)
Person: Jerónimo Castrillón
DBLP: Castrill=oacute=n:Jer=oacute=nimo
Contributed to:
20152014
201220102008
20172018
2019
20182020
2019Wrote 11 papers:
- DATE-2015-CastrillonTSSJA #manycore #programming #question
- Multi/many-core programming: where are we standing? (JC, LT, LS, WS, BHHJ, MAM, AP, RJ, VR, RL), pp. 1708–1717.
- DATE-2014-MurilloWCLA #automation #concurrent #constraints #debugging #detection
- Automatic detection of concurrency bugs through event ordering constraints (LGM, SW, JC, RL, GA), pp. 1–6.
- DAC-2012-CastrillonTLA
- Communication-aware mapping of KPN applications onto heterogeneous MPSoCs (JC, AT, RL, GA), pp. 1266–1271.
- DATE-2010-CastrillonVSSCLAM #analysis
- Trace-based KPN composability analysis for mapping simultaneous applications to MPSoC platforms (JC, RV, AS, WS, JC, RL, GA, HM), pp. 753–758.
- DAC-2008-CengCSSLAMIK #framework #named #parallel
- MAPS: an integrated framework for MPSoC application parallelization (JC, JC, WS, HS, RL, GA, HM, TI, HK), pp. 754–759.
- GPCE-2017-SusungiRCHCTSF #composition #generative #optimisation #towards
- Towards compositional and generative tensor optimizations (AS, NAR, JC, IH, AC, CT, JS, JF), pp. 169–175.
- GPCE-2018-SusungiRCCT #metaprogramming #optimisation
- Meta-programming for cross-domain tensor optimizations (AS, NAR, AC, JC, CT), pp. 79–92.
- SLE-2019-SchutzeC #composition #performance
- Efficient late binding of dynamic function compositions (LS, JC), pp. 141–151.
- CC-2018-ErtelGAC #compilation #performance
- Compiling for concise code and efficient I/O (SE, AG, JA, JC), pp. 104–115.
- CC-2020-BrauckmannGEC #graph #learning #modelling
- Compiler-based graph representations for deep learning models of code (AB, AG, SE, JC), pp. 201–211.
- Haskell-2019-ErtelARGC #composition #concurrent #data flow #monad #named #parallel #thread
- STCLang: state thread composition as a foundation for monadic dataflow parallelism (SE, JA, NAR, AG, JC), pp. 146–161.