TABLA: A unified template-based framework for accelerating statistical machine learning

Proceedings - International Symposium on High-Performance Computer Architecture

Volumn 2016-April, Issue , 2016, Pages 14-26

  Mahajan, Divya ^a   Park, Jongse ^a   Amaro, Emmanuel ^a   Sharma, Hardik ^a   Yazdanbakhsh, Amir ^a   Kim, Joon Kyung ^a   Esmaeilzadeh, Hadi ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCELERATION; ALGORITHMS; ARM PROCESSORS; ARTIFICIAL INTELLIGENCE; COMPUTER ARCHITECTURE; COMPUTER HARDWARE; COMPUTER PROGRAMMING LANGUAGES; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); GENERAL PURPOSE COMPUTERS; HARDWARE; HIGH LEVEL LANGUAGES; INTEGRATED CIRCUIT DESIGN; LEARNING SYSTEMS; LOGIC SYNTHESIS; OPTIMIZATION; PROGRAM PROCESSORS; RECONFIGURABLE HARDWARE; SUPERCOMPUTERS;

GENERAL PURPOSE PROCESSORS; HIGH-LEVEL ABSTRACTION; OBJECTIVE FUNCTIONS; OPTIMIZATION PROBLEMS; PERFORMANCE BENEFITS; STATISTICAL MACHINE LEARNING; STOCHASTIC GRADIENT DESCENT; STOCHASTIC OPTIMIZATION PROBLEMS;

LEARNING ALGORITHMS;

EID: 84965008656     PISSN: 15300897     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HPCA.2016.7446050     Document Type: Conference Paper

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