Difference between revisions of "hpc"
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'''Approximation algorithms for Kernel Methods on Multi-core CPUs and GPUs''' | '''Approximation algorithms for Kernel Methods on Multi-core CPUs and GPUs''' | ||
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We are exploring the opportunities of utilizing new architectures such as GPUs, multi-core processors, and distributed clusters (cloud computing) to efficiently solve research problems related to multimedia content analysis, large-scale data analysis, and machine learning techniques. | We are exploring the opportunities of utilizing new architectures such as GPUs, multi-core processors, and distributed clusters (cloud computing) to efficiently solve research problems related to multimedia content analysis, large-scale data analysis, and machine learning techniques. | ||
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* Fei Gao (MSc Student) | * Fei Gao (MSc Student) | ||
| − | * Taher Dameh | + | * [http://www.sfu.ca/~tdameh/ Taher Dameh] (MSc Student) |
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* M. Hussein and W. Abd-Almageed, [http://www.cs.umd.edu/~mhussein/papers/sc09_BAG_ha.pdf Efficient Band Approximation of Gram Matrices for Large Scale Kernel Methods on GPUs], In Proc. of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SuperComputing'09), Portland, OR, November 2009. | * M. Hussein and W. Abd-Almageed, [http://www.cs.umd.edu/~mhussein/papers/sc09_BAG_ha.pdf Efficient Band Approximation of Gram Matrices for Large Scale Kernel Methods on GPUs], In Proc. of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SuperComputing'09), Portland, OR, November 2009. | ||
| − | * [ http://www.mit.edu/~andoni/LSH/ Locality Sensitive Hashing] | + | * [http://www.mit.edu/~andoni/LSH/ Locality Sensitive Hashing] |
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| + | * [http://openmp.org/wp/ OpenMP] | ||
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| + | * [http://www.mcs.anl.gov/research/projects/mpich2/ MPICH2 (an MPI implementation)] | ||
| + | * [http://www.mit.edu/~andoni/LSH/manual.pdf Manual implementation for p-stable LSH ] | ||
== [[Private:hpc-discussion| On-going Research Problems and Discussion (Login Required)]] == | == [[Private:hpc-discussion| On-going Research Problems and Discussion (Login Required)]] == | ||
Latest revision as of 18:40, 21 July 2010
Approximation algorithms for Kernel Methods on Multi-core CPUs and GPUs
We are exploring the opportunities of utilizing new architectures such as GPUs, multi-core processors, and distributed clusters (cloud computing) to efficiently solve research problems related to multimedia content analysis, large-scale data analysis, and machine learning techniques.
People
- Mohamed Hefeeda (Assistant Professor)
- Wael Abd-Almageed (Assistant Research Scientist at UMD)
- Fei Gao (MSc Student)
- Taher Dameh (MSc Student)
References and Links
- M. Hussein and W. Abd-Almageed, Efficient Band Approximation of Gram Matrices for Large Scale Kernel Methods on GPUs, In Proc. of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SuperComputing'09), Portland, OR, November 2009.
