2026-05-28T22:16:50Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/144252026-02-03T12:08:58Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Villegas Fernández, Alejandro
author
Asenjo-Plaza, Rafael
author
González-Navarro, María Ángeles
author
Plata-González, Óscar Guillermo
author
Ubal, Rafael
author
Kaeli, David
2017-09-06T06:41:12Z
2017-09-06T06:41:12Z
2017-08-29
http://hdl.handle.net/10630/14425
http://orcid.org/0000-0002-1570-3863
Graphics Processing Units (GPUs) have become the accelerator of choice for data-parallel applications, enabling the execution of thousands of threads in a Single Instruction - Multiple Thread (SIMT) fashion. Using OpenCL terminology, GPUs offer a global memory space shared by all the threads in the GPU, as well as a low-latency local memory space shared by a subset of the threads. The latter is used as a scratchpad to improve the performance of the applications.
We propose GPU-LocalTM, a hardware transactional memory (TM), as an alternative to data locking mechanisms in local memory. GPU-LocalTM allocates transactional metadata in the existing memory resources, minimizing the storage requirements for TM support. In addition, it ensures forward progress through an automatic serialization mechanism. In our experiments, GPU-LocalTM provides up to 100X speedup over serialized execution.
eng
by-nc-nd
Ordenadores - Equipo de entrada y salida - Congresos
Hardware support for scratchpad memory transactions on GPU architectures
conference output
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