Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 9 of 9 for “"sparsity patterns"”.
-
Algorithm–Hardware Co-Design Of Digital Compute-In-Memory Architecture Supporting Flexible And Temporal N:M Sparsity
… for efficient inference, with structured N:M sparsity emerging as a promising method to reduce overhead. However, fixed sparsity configurations across layers and decoding steps can limit model expressivity and degrade accuracy, while supporting multiple configurations introduces challenges in …
-
Systematic Modeling and Design of Sparse Deep Neural Network Accelerators
… recognition, and language processing). The sparsity in such kernels has motivated the development of many sparse DNN accelerators. However, despite the abundant existing proposals, there has not been a systematic way to understand, model, and develop various sparse DNN accelerators. To …
-
Tailors: Accelerating Sparse Tensor Algebra by Overbooking Buffer Capacity
… to few opportunities for data reuse and varying sparsity patterns. Prior sparse tensor algebra accelerators have explored tiling sparse tensors to increase exploitable data reuse and improve throughput, but typically allocate tile size in a given buffer for the worst- case number of nonzero …
-
WACO: Learning workload-aware co-optimization of the format and schedule of a sparse tensor program
… co-optimizing the format and schedule of a given sparsity pattern in a sparse tensor program. A core challenge in this thesis is the design of a lightweight cost model that accurately predicts the runtime of a sparse tensor program by considering the sparsity pattern, the format, and the schedule. …
-
Automated Implementation of Advanced Electronic Structure Methods
… to reduced-scaling methods, which exploit the sparsity inherent in electronic correlation. We introduce a novel "tensor-of-tensors" data structure designed to manage the irregular sparsity patterns of Pair Natural Orbital (PNO) formulations. This development enables the first fully automated …
-
Modeling Strategies for Large Dimensional Vector Autoregressions
… outperforms Lasso-type methods in discovering sparsity patterns in AR coefficient matrices of VAR models. The performance of our 2-stage approach is also illustrated with three real data examples. Our second strategy for reducing the complexity of a large dimensional VAR model is based on a …
-
Generalizing smoothed aggregation-based algebraic multigrid
… coarsening and the choice of interpolation sparsity patterns. Unfortunately, the classic strength measure is only well-founded for M-matrices, leading us to develop a new measure based on local knowledge of both algebraically smooth error and the behavior of interpolation. Another limitation …
-
Sparse Support Matrix Machines for the Classification of Corrupted Data
… term which promotes the structural sparsity and shares similar sparsity patterns across multiple predictors. It is a spectral extension of the conventional elastic net that combines the property of low-rank and joint sparsity together, to deal with complex high dimensional noisy …