AccelerationHigher efficiency can only to a limited degree be offset by increased head count. New tools are needed to increase the throughput. The Headwave solution is the first to utilize the computational power of graphics card for processing resulting in unbeatable performance at a fraction of the cost of proprietary platforms.
"GPGPU" ParallelizationIn recent years we have seen the oil and gas industry embrace PC based clusters for computational purposes. Based on the Intel or AMD processors, clusters have made new algorithms feasible and reduced the turnaround time significantly.
To advance further, Headwave has employed commonly available technology in radical ways. By utilizing the processors ("GPUs") on graphics cards for processing, not only visualization, the Headwave solution is capable of providing results in real time or near real time - on standard, off the shelf G&G workstations.
Case : 200 x speed up in data processingAs a case in point for how algorithms on GPUs outperform CPUs, look at these numbers. Headwave contains a highly optimized algorithm for wavelet based compression and decompression of seismic data. Implemented and optimized on the CPU, we are able to compress approximately 10MB/sec. Headwave's implementation on the GPU exploits the parallel capabilities of the GPU, providing more than 2GB/sec - a performance speed up of 200 times.
Other commonly used algorithms/filters in prestack and poststack data processing that we have implemented, run anywhere from 10 to 70 times faster on the GPU than on the CPU. This results in reduced turn-around time, but also allows for faster parameterization.
HardwareThere are a number of acceleration devices available on the market. Only one solution has so far made it into practically every workstation : The graphics card. Every G&G workstation needs a powerful graphics card.
Recommended Graphics Cards
See Supported Systems
Nvidia TeslaNvidia launched the Tesla series in 2007 and Headwave was one of the first to fully embrace the compute capabilities that Nvidia made available in their graphics cards and specific accelerator cards (Tesla units).
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