Data optimization: allocation of arrays to reduce communication on SIMD machines
Journal of Parallel and Distributed Computing - Massively parallel computation
A static performance estimator to guide data partitioning decisions
PPOPP '91 Proceedings of the third ACM SIGPLAN symposium on Principles and practice of parallel programming
The DINO parallel programming language
Journal of Parallel and Distributed Computing
The data alignment phase in compiling programs for distributed-memory machines
Journal of Parallel and Distributed Computing
Supporting fine-grain computation on distributed memory parallel computers
Supporting fine-grain computation on distributed memory parallel computers
Automatic data mapping for distributed-memory parallel computers
Automatic data mapping for distributed-memory parallel computers
Compiling Fortran D for MIMD distributed-memory machines
Communications of the ACM
Global optimizations for parallelism and locality on scalable parallel machines
PLDI '93 Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
PARADIGM: a compiler for automatic data distribution on multicomputers
ICS '93 Proceedings of the 7th international conference on Supercomputing
Compiling Functional Parallelism on Distributed-Memory Systems
IEEE Parallel & Distributed Technology: Systems & Technology
Software—Practice & Experience
Compiler techniques for data partitioning of sequentially iterated parallel loops
ICS '90 Proceedings of the 4th international conference on Supercomputing
Distributed filaments: efficient fine-grain parallelism on a cluster of workstations
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Scientific Programming
Accurate data redistribution cost estimation in software distributed shared memory systems
PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
Scaling irregular parallel codes with minimal programming effort
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
LCR '98 Selected Papers from the 4th International Workshop on Languages, Compilers, and Run-Time Systems for Scalable Computers
Integrated code and data placement in two-dimensional mesh based chip multiprocessors
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
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Programming distributed-memory machines requires careful placement of data to balance the computational load among the nodes and minimize excess data movement between the nodes. Most current approaches to data placement require the programmer or compiler to place data initially and then possibly to move it explicitly during a computation. This paper describes a new, adaptive approach. It is implemented in the Adapt system, which takes an initial data placement, efficiently monitors how well it performs, and changes the placement whenever the monitoring indicates that a different placement would perform better. Adapt frees the programmer from having to specify data placements, and it can use run-time information to find better placements than compilers. Moreover, Adapt automatically supports a "variable block'' placement, which is especially useful for applications with nearest-neighbor communication but an imbalanced workload. For applications in which the best data placement varies dynamically, using Adapt can lead to better performance than using any statically determined data placement.