Researchers explore an approach to using general purpose parallel computers which involves mapping hardware resources onto computations instead of mapping computations onto hardware. Problems such as processor allocation, task scheduling and load balancing, which have traditionally proven to be challenging, change significantly under this approach and may become amenable to new attacks. Researchers describe the implementation of this approach used by the FFP Machine whose computation and communication resources are repeatedly partitioned into disjoint groups that match the needs of available tasks from moment to moment. Several consequences of this system are examined
Many problems in Artificial Intelligence involve traversing large search-spaces. Such problems typic...
A set of communication operations is defined, which allows a form of task parallelism to be achieved...
International audienceComputing in parallel means performing computation simultaneously, this genera...
The general problem studied is that of segmenting or partitioning programs for distribution across a...
Across the landscape of computing, parallelism within applications is increasingly important in orde...
New mapping algorithms for domain oriented data-parallel computations, where the workload is distrib...
Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: ...
When multiple jobs compete for processing resources on a parallel computer, the operating system ker...
We describe an approach to parallel compilation that seeks to harness the vast amount of fine-grain ...
To compile programs for message passing architectures and to obtain good performance on NUMA archit...
This paper is submitted for review to the Parallel Computing special issue for HCW and HeteroPar 16 ...
Load balancing increases the efficient usage of existing resources for parallel and distributed appl...
The increasing density of VLSI circuits has motivated research into ways to utilize large area budge...
It has been suggested that non-scientific code has very little parallelism not already exploited by ...
One of the most important issues in parallel processing is the mapping of workload to processors. Th...
Many problems in Artificial Intelligence involve traversing large search-spaces. Such problems typic...
A set of communication operations is defined, which allows a form of task parallelism to be achieved...
International audienceComputing in parallel means performing computation simultaneously, this genera...
The general problem studied is that of segmenting or partitioning programs for distribution across a...
Across the landscape of computing, parallelism within applications is increasingly important in orde...
New mapping algorithms for domain oriented data-parallel computations, where the workload is distrib...
Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: ...
When multiple jobs compete for processing resources on a parallel computer, the operating system ker...
We describe an approach to parallel compilation that seeks to harness the vast amount of fine-grain ...
To compile programs for message passing architectures and to obtain good performance on NUMA archit...
This paper is submitted for review to the Parallel Computing special issue for HCW and HeteroPar 16 ...
Load balancing increases the efficient usage of existing resources for parallel and distributed appl...
The increasing density of VLSI circuits has motivated research into ways to utilize large area budge...
It has been suggested that non-scientific code has very little parallelism not already exploited by ...
One of the most important issues in parallel processing is the mapping of workload to processors. Th...
Many problems in Artificial Intelligence involve traversing large search-spaces. Such problems typic...
A set of communication operations is defined, which allows a form of task parallelism to be achieved...
International audienceComputing in parallel means performing computation simultaneously, this genera...