Add to ORKGData layouts play a crucial role in determining the perfor-mance of a given application running on a given architec-ture. Existing parallel programming frameworks for both multicore and heterogeneous systems leave the onus of se-lecting a data layout to the programmer. Therefore, shifting the burden of data layout selection to optimizing compil-ers can greatly enhance programmer productivity and ap-plication performance. In this work, we introduce ADHA: a two-level hierarchal formulation of the data layout problem for modern heterogeneous architectures. We have created a reference implementation of ADHA in the Heterogeneous Habanero-C (H2C) parallel programming system. ADHA shows significant performance benefits of up to 6.92 × com-pared to...
Computer systems have become more heterogeneous due to the breakdown of Dennard Scaling and the rapi...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/1...
Heterogeneous computing platforms support the traditional types of parallelism, such as e.g., ins...
Part 2: Parallel and Multi-Core TechnologiesInternational audienceApplying appropriate data structur...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
High Performance Fortran (HPF) is rapidly gaining acceptance as a language for parallel programming....
Abstract—There has been a growing trend in using heteroge-neous systems with CPUs and GPUs to solve ...
Besides the algorithm selection, the data layout choice is the key intellectual step in writing an e...
Integrated Heterogeneous System (IHS) processors pack throughput-oriented General-Purpose Graphics P...
With the end of Dennard scaling and emergence of dark silicon, the bets are high on heterogeneous ar...
The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet ef...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...
The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet ef...
Despite the fact that GPU was originally intended to be as a co-processor specializing in graphics r...
With the advent of accelerators and architectures, researchers are faced with a daunting task to por...
Computer systems have become more heterogeneous due to the breakdown of Dennard Scaling and the rapi...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/1...
Heterogeneous computing platforms support the traditional types of parallelism, such as e.g., ins...
Part 2: Parallel and Multi-Core TechnologiesInternational audienceApplying appropriate data structur...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
High Performance Fortran (HPF) is rapidly gaining acceptance as a language for parallel programming....
Abstract—There has been a growing trend in using heteroge-neous systems with CPUs and GPUs to solve ...
Besides the algorithm selection, the data layout choice is the key intellectual step in writing an e...
Integrated Heterogeneous System (IHS) processors pack throughput-oriented General-Purpose Graphics P...
With the end of Dennard scaling and emergence of dark silicon, the bets are high on heterogeneous ar...
The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet ef...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...
The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet ef...
Despite the fact that GPU was originally intended to be as a co-processor specializing in graphics r...
With the advent of accelerators and architectures, researchers are faced with a daunting task to por...
Computer systems have become more heterogeneous due to the breakdown of Dennard Scaling and the rapi...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/1...
Heterogeneous computing platforms support the traditional types of parallelism, such as e.g., ins...