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pro vyhledávání: '"Garg, Raveesh"'
PipeOrgan: Efficient Inter-operation Pipelining with Flexible Spatial Organization and Interconnects
Because of the recent trends in Deep Neural Networks (DNN) models being memory-bound, inter-operator pipelining for DNN accelerators is emerging as a promising optimization. Inter-operator pipelining reduces costly on-chip global memory and off-chip
Externí odkaz:
http://arxiv.org/abs/2405.01736
HPC applications are critical in various scientific domains ranging from molecular dynamics to chemistry to fluid dynamics. Conjugate Gradient (CG) is a popular application kernel used in iterative linear HPC solvers and has applications in numerous
Externí odkaz:
http://arxiv.org/abs/2303.11499
Autor:
Muñoz-Martínez, Francisco, Garg, Raveesh, Abellán, José L., Pellauer, Michael, Acacio, Manuel E., Krishna, Tushar
Sparsity is a growing trend in modern DNN models. Existing Sparse-Sparse Matrix Multiplication (SpMSpM) accelerators are tailored to a particular SpMSpM dataflow (i.e., Inner Product, Outer Product or Gustavsons), that determines their overall effici
Externí odkaz:
http://arxiv.org/abs/2301.10852
Autor:
Qin, Eric, Garg, Raveesh, Bambhaniya, Abhimanyu, Pellauer, Michael, Parashar, Angshuman, Rajamanickam, Sivasankaran, Hao, Cong, Krishna, Tushar
Recently, numerous sparse hardware accelerators for Deep Neural Networks (DNNs), Graph Neural Networks (GNNs), and scientific computing applications have been proposed. A common characteristic among all of these accelerators is that they target tenso
Externí odkaz:
http://arxiv.org/abs/2201.08916
Autor:
Garg, Raveesh, Qin, Eric, Muñoz-Martínez, Francisco, Guirado, Robert, Jain, Akshay, Abadal, Sergi, Abellán, José L., Acacio, Manuel E., Alarcón, Eduard, Rajamanickam, Sivasankaran, Krishna, Tushar
Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applications in cloud and HPC. Owing to their unique compute and memory charac
Externí odkaz:
http://arxiv.org/abs/2103.07977