Communication (data movement) often dominates a computation's runtime and energy costs, motivating organizing an algorithm's operations to minimize communication. We study communication costs of a class of algorithms including many-body and matrix/tensor computations and, more generally, loop nests operating on array variables subscripted by linear functions of the loop iteration vector. We use this algebraic relationship between variables and operations to derive communication lower bounds for these algorithms. We also discuss communication-optimal implementations that attain these bounds
In distributed optimization and machine learning, multiple nodes coordinate to solve large problems....
Communication is a universal process by which two or more individuals exchange information. A commun...
We initiate a study of tradeoffs between communication and computation in well-known communication m...
this paper, we propose a communication cost reduction computes rule for irregular loop partitioning...
The movement of data (communication) between levels of a memory hierarchy, or between parallel proce...
In this paper, we propose a communication cost reduction computes rule for irregular loop partitioni...
In this paper we study the tradeoff between parallelism and communication cost in a map-reduce compu...
Dense linear algebra computations are essential to nearly every problem in scientific computing and ...
Abstract. This paper introduces communicating branching programs and develops a general technique fo...
Reducing communication overhead is extremely important in distributed-memory message-passing archite...
We present lower bounds on the amount of communication that matrix multiplication algorithms must pe...
In most cases of distributed memory computations, node programs are executed on processors according...
Abstract. In most cases of distributed memory computations, node programs are executed on processors...
AbstractSome generalized communication modes enabling the dissemination of information among process...
We consider a number of fundamental statistical and graph problems in the message-passing model, whe...
In distributed optimization and machine learning, multiple nodes coordinate to solve large problems....
Communication is a universal process by which two or more individuals exchange information. A commun...
We initiate a study of tradeoffs between communication and computation in well-known communication m...
this paper, we propose a communication cost reduction computes rule for irregular loop partitioning...
The movement of data (communication) between levels of a memory hierarchy, or between parallel proce...
In this paper, we propose a communication cost reduction computes rule for irregular loop partitioni...
In this paper we study the tradeoff between parallelism and communication cost in a map-reduce compu...
Dense linear algebra computations are essential to nearly every problem in scientific computing and ...
Abstract. This paper introduces communicating branching programs and develops a general technique fo...
Reducing communication overhead is extremely important in distributed-memory message-passing archite...
We present lower bounds on the amount of communication that matrix multiplication algorithms must pe...
In most cases of distributed memory computations, node programs are executed on processors according...
Abstract. In most cases of distributed memory computations, node programs are executed on processors...
AbstractSome generalized communication modes enabling the dissemination of information among process...
We consider a number of fundamental statistical and graph problems in the message-passing model, whe...
In distributed optimization and machine learning, multiple nodes coordinate to solve large problems....
Communication is a universal process by which two or more individuals exchange information. A commun...
We initiate a study of tradeoffs between communication and computation in well-known communication m...