FPGA and GPU-based acceleration of ML workloads on Amazon cloud - A case study using gradient boosted decision tree library.
Maxim ShepovalovVenkatesh AkellaPublished in: Integr. (2020)
Keyphrases
- decision trees
- random forests
- map reduce
- parallel computation
- cloud computing
- maximum likelihood
- case study
- hardware implementation
- cloud platform
- predictive accuracy
- high speed
- decision tree algorithm
- database systems
- field programmable gate array
- edge detection
- low cost
- logistic regression
- computer systems
- decision tree induction
- random forest
- access patterns
- decision tree classifiers
- real time
- gradient information
- real time image processing
- graphics hardware
- fpga implementation
- test bed
- naive bayes
- classification rules
- hardware architecture
- verilog hdl
- training data
- decision tree learning
- decision forest
- parallel implementation
- times faster
- limited memory
- decision table
- parallel processing
- ensemble methods
- virtual machine
- learning algorithm
- machine learning
- graphics processors
- cloud computing environment
- hardware architectures
- database