hyPACK-2013 HPC GPU Cluster - Application Kernels
Video Processing
Video Processing :
The graphics performance of specialized software, e.g. scientific software,
image manipulation, video decoders/encoders, games that make GPU performance
is pretty important. In video processing, the GPU processor takes a video
stream and perform image processing operations (effects) on its content
using graphic APIs to generate a video stream that can be presented to the
display in real time. The scalability of video processing can be achieved
when multiple video streams are enhanced to combine multiple video streams
together to produce a singel output stream.
On GPUs, hardware decoding with OpenVideo Decode API have been used. Many
decoding libraries exist for the various platforms supporting video
devcode using the power of CPU Multi-core processors. Video processing
effects can be carried out on GPU. The CUDA enabled NVIDIA GPU or OpenCL
can be used to decode video on the GPU. Working in OpenCL and output video
display using OpenGL is one programming paradigm.
To decide a frame of video, we must fist initialize the decoding framework and request
tha tit open the file. The decode framework will then decode frame of video
in the designated format. The process of data is done using OpenCL.
Important steps of Video Processing will be discussed in laboratory sessions.
HPC GPU Cluster :
In hyPACK-2013 workshop, a prototype HPC GPU cluster (CUDA /OpenCL enabled NVIDIA GPUs
& AMD-ATI OpenCL Prog. env) is used to solve
application kernels, that are based on Heterogenous
programming model
In this workshop, programming and performance issues for applications on
HPC GPU Clusters will be discussed.
In laboratory session, a prototype Hybrid Heterogneous HPC GPU Cluster is made available,
which can address some of the heterogeneous computing workloads.
The HPC GPU Cluster can be made "adaptive" to the
application it is running, assigning the most effective resources in real-time as
per application demands, without requiring modifications to the application. One of the objectives of HPC GPU Cluster (hybrid computing system) is
to allocate resources of CPUs & GPUs in an optimal way to solve applications of different
characterstics.
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