Analyzing the energy-efficiency of sparse matrix multiplication on heterogeneous systems: A comparative study of GPU, Xeon Phi and FPGA.
Heiner GiefersPeter W. J. StaarCostas BekasChristoph HagleitnerPublished in: ISPASS (2016)
Keyphrases
- energy efficiency
- heterogeneous systems
- matrix multiplication
- power consumption
- parallel computing
- energy consumption
- wireless sensor networks
- field programmable gate array
- high performance computing
- parallel architectures
- data center
- sensor networks
- real time
- distributed architecture
- response time
- message passing
- routing protocol
- computing systems
- smart home
- distributed memory
- application developers
- graphics processing units
- processing units
- parallel processing
- web services
- matrix factorization
- low cost
- hardware implementation
- hardware design
- massively parallel
- shared memory
- databases
- sensor nodes
- parallel computers
- database
- software developers
- parallel programming
- parallel machines
- data transmission
- context aware
- probabilistic model
- recommender systems