S. Krishnan

Publications8
h-index6
Citations389
Highly Influential Citations19
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Synthesis of High-Performance Parallel Programs for a Class of ab Initio Quantum Chemistry Models
TLDR
This paper provides an overview of a program synthesis system for a class of quantum chemistry computations, expressible as a set of tensor contractions and arise in electronic structure modeling.
View on IEEE
Automatic code generation for many-body electronic structure methods: the tensor contraction engine
TLDR
An overview of the Tensor Contraction Engine (TCE), a unique effort to address issues of both productivity and performance through automatic code generation that acts like an optimizing compiler.
View on Taylor & Francis
Efficient synthesis of out-of-core algorithms using a nonlinear optimization solver
View on IEEE
Global communication optimization for tensor contraction expressions under memory constraints
TLDR
An approach to identify the best combination of loop fusion and data partitioning that minimizes inter-processor communication cost without exceeding the per-processor memory limit is developed.
View on IEEE
Data Locality Optimization for Synthesis of Efficient Out-of-Core Algorithms
TLDR
This paper describes an approach to synthesis of efficient out-of-core code for a class of imperfectly nested loops that represent tensor contraction computations that combines loop fusion with loop tiling and uses a performance-model driven approach toloop tiling for the generation of out- of-corecode.
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Memory-Constrained Data Locality Optimization for Tensor Contractions
TLDR
An optimization framework to search among a space of fusion and tiling choices to minimize the data movement overhead is developed and is demonstrated on a computation representative of a component used in quantum chemistry suites.
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Efficient Synthesis of Out-of-Core Algorithms Using a Nonlinear Optimization Solver
TLDR
This work addresses the problem of efficient out-of-core code generation for a special class of imperfectly nested loops encoding tensor contractions on arrays too large to fit in physical memory by forming the problem as a nonlinear optimization problem and using a discrete constraint solver to generate optimized code.
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Electronic Structure Methods: The Tensor Contraction Engine ⁄