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GTC ON-DEMAND

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Abstract:
Scientific simulations typically store just a small fraction of their computed timesteps--as few as one in 500--due to I/O and storage limitations. Previous work has demonstrated in situ software-based compression, but at the cost of compute cycles that simulation scientists are loath to sacrifice. We propose the use of the special-purpose video processing unit (VPU), currently unutilized in the HPC context, for inexpensive lossy encoding. Our work demonstrates that video encoding quality is suitable for volumes and recommends encoder settings. We'll show that data can be encoded in parallel with a hybrid CPU/GPU computation with minimal impact on run time. We'll also demonstrate that decoding is fast enough for on-the-fly decompression during analysis.
Scientific simulations typically store just a small fraction of their computed timesteps--as few as one in 500--due to I/O and storage limitations. Previous work has demonstrated in situ software-based compression, but at the cost of compute cycles that simulation scientists are loath to sacrifice. We propose the use of the special-purpose video processing unit (VPU), currently unutilized in the HPC context, for inexpensive lossy encoding. Our work demonstrates that video encoding quality is suitable for volumes and recommends encoder settings. We'll show that data can be encoded in parallel with a hybrid CPU/GPU computation with minimal impact on run time. We'll also demonstrate that decoding is fast enough for on-the-fly decompression during analysis.  Back
 
Topics:
HPC and AI, 5G & Edge, In-Situ & Scientific Visualization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8561
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