Publications

Systems and methods for selective expansive recursive tensor analysis

A system for performing tensor decomposition in a selective expansive and/or recursive manner, a tensor is decomposed into a specified number of components, and one or more tensor components are selected for further decomposition. For each selected component, the significant elements thereof are identified, and using the indices of the

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Systems and methods for scalable hierarchical polyhedral compilation

A system for compiling programs for execution thereof using a hierarchical processing system having two or more levels of memory hierarchy can perform memory-level-specific optimizations, without exceeding a specified maximum compilation time. To this end, the compiler system employs a polyhedral model and limits the dimensions of a polyhedral program

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Automatic Mapping and Optimization to Kokkos with Polyhedral Compilation

In the post-Moore’s Law era, the quest for exascale computing has resulted in diverse hardware architecture trends, including novel custom and/or specialized processors to accelerate the systems, asynchronous or self-timed computing cores, and near-memory computing architectures. To contend with such heterogeneous and complex hardware targets, there have been advanced software

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Large–scale Sparse Tensor Decomposition Using a Damped Gauss–Newton Method

CANDECOMP/PARAFAC (CP) tensor decomposition is a popular unsupervised machine learning method with numerous applications. This process involves modeling a high–dimensional, multi–modal array (a tensor) as the sum of several low–dimensional components. In order to decompose a tensor, one must solve an optimization problem, whose objective is often given by the

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HACCLE: An Ecosystem for Building Secure Multi-Party Computations

Cryptographic techniques have the potential to enable distrusting parties to collaborate in fundamentally new ways, but their practical implementation poses numerous challenges. An important class of such cryptographic techniques is known as secure multi-party computation (MPC). In an effort to provide an ecosystem for building secure MPC applications using higher

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Systems and methods for stencil amplification

In a sequence of major computational steps or in an iterative computation, a stencil amplifier can increase the number of data elements accessed from one or more data structures in a single major step or iteration, thereby decreasing the total number of computations and/or communication operations in the overall sequence

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