We present ReLATE, a deep reinforcement learning framework for automatically constructing an efficient sparse tensor format
We present ReLATE, a deep reinforcement learning framework for automatically constructing an efficient sparse tensor format
We present a custom geometric multigrid preconditioned conjugate gradient method that applies summation-by-parts(SBP)-preserving interpolations and a custom matrix-free GPU kernel that achieves up to 5x speedup compared to solvers from PETSc and AmgX
We demonstrate the efficiency and performance-portability of encoding sparse tensors in a linearized format
We discuss using high-performance tensor decomposition for topic modeling and malware detection
We discuss our experience in optimizing the CP and Tucker decomposition algorithms for sparse datasets on a distributed system.
We discuss our experience in optimizing the CP and Tucker decomposition algorithms for sparse datasets on a distributed system.
We share our experience in using tensor decomposition for detecting malware
We discuss our experience in optimizing the non-negative Tucker decomposition for sparse datasets on a distributed system.
We discuss our experience in optimizing the CP and Tucker decomposition algorithms for sparse datasets on a distributed system.