Travelled to:1 × Hungary
1 × Italy
1 × South Africa
1 × Turkey
2 × India
6 × USA
Collaborated with:M.Maggio A.Filieri S.Misailovic M.C.Rinard H.Zhang S.Sidiroglou C.Imes N.Mishra J.D.Lafferty ∅ A.Agarwal M.D.Santambrogio L.Bergstrom J.E.Miller S.Sidiroglou-Douskos A.V.Papadopoulos Bernard Dickens III H.S.Gunawi A.J.Feldman J.Eastep M.Carbin S.Wang C.Li S.Lu William Sentosa Achmad Imam Kistijantoro G.Li X.Chen G.Sun Y.Liu Y.Wang H.Yang F.Sironi D.B.Bartolini S.Campanoni F.Cancare D.Sciuto Yunong Shi Nelson Leung Pranav Gokhale Zane Rossi David I. Schuster F.T.Chong M.I.Gordon W.Thies M.Karczmarek J.Lin A.S.Meli A.A.Lamb C.Leger J.Wong D.Maze S.P.Amarasinghe J.Holt G.Kurian E.Lau S.M.Neuman M.E.Sinangil Y.Sinangil A.P.Chandrakasan S.Devadas
Talks about:perform (7) softwar (5) comput (5) control (4) energi (4) self (4) power (3) autom (3) adapt (3) understand (2)
Person: Henry Hoffmann
DBLP: Hoffmann:Henry
Contributed to:
2015
2015
2015
2015
20142012201120112010
2010
20102002
20162017201620182019Wrote 20 papers:
- ASPLOS-2015-MishraZLH #approach #constraints #energy #modelling #performance #probability #visual notation
- A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints (NM, HZ, JDL, HH), pp. 267–281.
- DAC-2015-LiCSHLWY #hybrid #power management
- A STT-RAM-based low-power hybrid register file for GPGPUs (GL, XC, GS, HH, YL, YW, HY), p. 6.
- ESEC-FSE-2015-FilieriHM #adaptation #automation #design #multi #self
- Automated multi-objective control for self-adaptive software design (AF, HH, MM), pp. 13–24.
- SOSP-2015-Hoffmann #approximate #energy #named
- JouleGuard: energy guarantees for approximate applications (HH), pp. 198–214.
- ICSE-2014-FilieriHM #adaptation #automation #design #self
- Automated design of self-adaptive software with control-theoretical formal guarantees (AF, HH, MM), pp. 299–310.
- DAC-2012-HoffmannHKLMMNSSACD #self
- Self-aware computing in the Angstrom processor (HH, JH, GK, EL, MM, JEM, SMN, MES, YS, AA, APC, SD), pp. 259–264.
- DAC-2012-SironiBCCHSS #adaptation #named #operating system #performance #self
- Metronome: operating system level performance management via self-adaptive computing (FS, DBB, SC, FC, HH, DS, MDS), pp. 856–865.
- ASPLOS-2011-HoffmannSCMAR #power management
- Dynamic knobs for responsive power-aware computing (HH, SS, MC, SM, AA, MCR), pp. 199–212.
- ESEC-FSE-2011-Sidiroglou-DouskosMHR #performance #trade-off
- Managing performance vs. accuracy trade-offs with loop perforation (SSD, SM, HH, MCR), pp. 124–134.
- ICSE-2010-MisailovicSHR #profiling #quality
- Quality of service profiling (SM, SS, HH, MCR), pp. 25–34.
- OOPSLA-2010-RinardHMS #analysis #comprehension #statistics
- Patterns and statistical analysis for understanding reduced resource computing (MCR, HH, SM, SS), pp. 806–821.
- PPoPP-2010-HoffmannESMA #health #performance
- Application heartbeats for software performance and health (HH, JE, MDS, JEM, AA), pp. 347–348.
- ASPLOS-2002-GordonTKLMLLWHMA #architecture #compilation
- A stream compiler for communication-exposed architectures (MIG, WT, MK, JL, ASM, AAL, CL, JW, HH, DM, SPA), pp. 291–303.
- FSE-2016-ImesBH #energy #interface #monitoring #runtime
- A portable interface for runtime energy monitoring (CI, LB, HH), pp. 968–974.
- ESEC-FSE-2017-MaggioPFH #automation #multi #using
- Automated control of multiple software goals using multiple actuators (MM, AVP, AF, HH), pp. 373–384.
- ASPLOS-2016-ZhangH #comparison #hardware #hybrid #performance
- Maximizing Performance Under a Power Cap: A Comparison of Hardware, Software, and Hybrid Techniques (HZ, HH), pp. 545–559.
- ASPLOS-2018-DickensGFH #encryption #named #performance #using
- StrongBox: Confidentiality, Integrity, and Performance using Stream Ciphers for Full Drive Encryption (BDI, HSG, AJF, HH), pp. 708–721.
- ASPLOS-2018-MishraILH #energy #latency #learning #named #predict
- CALOREE: Learning Control for Predictable Latency and Low Energy (NM, CI, JDL, HH), pp. 184–198.
- ASPLOS-2018-WangLHLSK #comprehension
- Understanding and Auto-Adjusting Performance-Sensitive Configurations (SW, CL, HH, SL, WS, AIK), pp. 154–168.
- ASPLOS-2019-ShiLGRSHC #compilation #quantum
- Optimized Compilation of Aggregated Instructions for Realistic Quantum Computers (YS, NL, PG, ZR, DIS, HH, FTC), pp. 1031–1044.