AbstractThe sparse evaluation graph has emerged over the past several years as an intermediate representation that captures the dataflow information in a program compactly and helps perform dataflow analysis efficiently. The contributions of this paper are three-fold: •We present a linear time algorithm for constructing a variant of the sparse evaluation graph for any dataflow analysis problem. Our algorithm has two advantages over previous algorithms for constructing sparse evaluation graphs. First, it is simpler to understand and implement. Second, our algorithm generates a more compact representation than the one generated by previous algorithms. (Our algorithm is also as efficient as the most efficient known algorithm for the problem.)•...
We introduce a framework for sparsity structures defined via graphs. Our approach is flexible and ge...
In this paper we present two combinatorial algorithms for Sparsest Cut which achieve an O(logn) appr...
Many important applications are organized around long-lived, irregular sparse graphs (e.g., data an...
AbstractThe sparse evaluation graph has emerged over the past several years as an intermediate repre...
Data-flow analyses usually associate information with control flow regions. Informally, if these reg...
Program analysis plays a major role in advanced compilers, yet traditional approaches to data flow a...
Recently, Static Single Assignment Form and Sparse Evaluation Graphs have been advanced for the effi...
abstract: Sparse learning is a powerful tool to generate models of high-dimensional data with high i...
While there exists a growing literature dealing with the interpolation of sparse polynomials, fewer ...
There has been substantial interest from both computer science and statistics in developing methods ...
Data flow analysis based on an incremental approach may require that the dominator tree be correctly...
Illustrating how to implement efficient data structures for sparse graphs. When searching for graph...
The problem of finding an implicit representation for a graph such that vertex adjacency can be test...
Finding the transitive closure of a graph is a fundamental graph problem where another graph is obta...
We introduce a framework for sparsity structures defined via graphs. Our approach is flexible and ge...
We introduce a framework for sparsity structures defined via graphs. Our approach is flexible and ge...
In this paper we present two combinatorial algorithms for Sparsest Cut which achieve an O(logn) appr...
Many important applications are organized around long-lived, irregular sparse graphs (e.g., data an...
AbstractThe sparse evaluation graph has emerged over the past several years as an intermediate repre...
Data-flow analyses usually associate information with control flow regions. Informally, if these reg...
Program analysis plays a major role in advanced compilers, yet traditional approaches to data flow a...
Recently, Static Single Assignment Form and Sparse Evaluation Graphs have been advanced for the effi...
abstract: Sparse learning is a powerful tool to generate models of high-dimensional data with high i...
While there exists a growing literature dealing with the interpolation of sparse polynomials, fewer ...
There has been substantial interest from both computer science and statistics in developing methods ...
Data flow analysis based on an incremental approach may require that the dominator tree be correctly...
Illustrating how to implement efficient data structures for sparse graphs. When searching for graph...
The problem of finding an implicit representation for a graph such that vertex adjacency can be test...
Finding the transitive closure of a graph is a fundamental graph problem where another graph is obta...
We introduce a framework for sparsity structures defined via graphs. Our approach is flexible and ge...
We introduce a framework for sparsity structures defined via graphs. Our approach is flexible and ge...
In this paper we present two combinatorial algorithms for Sparsest Cut which achieve an O(logn) appr...
Many important applications are organized around long-lived, irregular sparse graphs (e.g., data an...