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MVAPICH2-GPU: optimized GPU to GPU communication for InfiniBand clusters

Computer Science - Research and Development, 2011
Data parallel architectures, such as General Purpose Graphics Units (GPGPUs) have seen a tremendous rise in their application for High End Computing. However, data movement in and out of GPGPUs remain the biggest hurdle to overall performance and programmer productivity.
Hao Wang 0002   +5 more
openaire   +2 more sources

GMMSP on GPU

Journal of Real-Time Image Processing, 2018
Superpixel segmentation is a fundamental task in computer vision. Existing works contribute to superpixel segmentation either by improving segmentation accuracy or by reducing execution time. The former modifies existing models or develops new models to improve accuracy. The latter accelerates existing implementations or reduces algorithm complexity to
Zhihua Ban   +2 more
openaire   +1 more source

GPU Rainfall

Journal of Graphics Tools, 2008
International ...
Rousseau, Pierre   +2 more
openaire   +2 more sources

GPU-Ether: GPU-native Packet I/O for GPU Applications on Commodity Ethernet

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, 2021
Despite the advent of various network enhancement technologies, it is yet a challenge to provide high-performance networking for GPU-accelerated applications on commodity Ethernet. Kernel-bypass I/O, such as DPDK or netmap, which is normally optimized for host memory-based CPU applications, has limitations on improving the performance of GPU ...
Changue Jung   +4 more
openaire   +2 more sources

GPU Objects

2006
Points, lines, and polygons have been the fundamental primitives in graphics. Graphics hardware is optimized to handle them in a pipeline. Other objects are converted to these primitives before rendering. Programmable GPUs have made it possible to introduce a wide class of computations on each vertex and on each fragment.
Sunil Mohan Ranta   +2 more
openaire   +1 more source

GPU-CC

Proceedings of the 16th International Workshop on Software and Compilers for Embedded Systems, 2013
Us have evolved to programmable, energy efficient compute accelerators for massively parallel applications. Still, compute power is lost in many applications because of cycles spent on data movement and control instead of computations on actual data. Additional cycles can be lost as well on pipeline stalls due to long latency operations.
Braak, van den, G.J.W., Corporaal, H.
openaire   +1 more source

GPU snapshot

Proceedings of the ACM International Conference on Supercomputing, 2019
Future High-Performance Computing (HPC) systems will likely be composed of accelerator-dense heterogeneous computers because accelerators are able to deliver higher performance at lower costs, socket counts and energy consumption. Such accelerator-dense nodes pose a reliability challenge because preserving a large amount of state within accelerators ...
Kyushick Lee   +5 more
openaire   +1 more source

GPU merge path

Proceedings of the 26th ACM international conference on Supercomputing, 2012
Graphics Processing Units (GPUs) have become ideal candidates for the development of fine-grain parallel algorithms as the number of processing elements per GPU increases. In addition to the increase in cores per system, new memory hierarchies and increased bandwidth have been developed that allow for significant performance improvement when ...
Oded Green   +2 more
openaire   +1 more source

GPUs a closer look

ACM SIGGRAPH 2008 classes, 2008
A gamer wanders through a virtual world rendered in nearcinematic detail. Seconds later, the screen fills with a 3D explosion, the result of unseen enemies hiding in physically accurate shadows. Disappointed, the user exits the game and returns to a computer desktop that exhibits the stylish 3D look-and-feel of a modern window manager.
Kayvon Fatahalian, Mike Houston
openaire   +3 more sources

GPU-SM: shared memory multi-GPU programming

Proceedings of the 8th Workshop on General Purpose Processing using GPUs, 2015
Discrete GPUs in modern multi-GPU systems can transparently access each other's memories through the PCIe interconnect. Future systems will improve this capability by including better GPU interconnects such as NVLink. However, remote memory access across GPUs has gone largely unnoticed among programmers, and multi-GPU systems are still programmed like ...
Javier Cabezas   +4 more
openaire   +1 more source

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