data processing & interpretation 41
Fig. 4. Comparison of a Tesla C1060 workstation with legacy systems. The table shows the speed improvement of
GPU Accelerated processes on a 1GB dataset running on a compute only (no screen connection) Tesla C1060 GPU
Card as a Secondary GPU versus the same process running on a range of workstations.
clusters. A typical oil and gas application would use giving four teraflops for a maximum power consumption
NVIDIA’s Tesla range. of 800W. This can easily be scaled up to cope with even
The latest chip for workstations, the Tesla C1060, is the most intensive processing tasks.
capable of one teraflop of processing power, and has 4GB GPU based servers are cheaper than CPUs for
of dedicated memory. It has 240 processing cores and equivalent processing power, and have much lower power
uses just 160W (Fig. 6). consumption, reducing running costs.
A typical workstation could use four GPUs, giving four
teraflops of processing power, equivalent to around 60
CPUs.
NVIDIA has just brought out a 1U rack-mount system,
the S1070, that features four Tesla GPUs in a single unit, N
VIDIA and Supermicro have also developed
a two teraflop 1U server that uses two
quad core Intel Xeon processors with two
C1060 NVIDIA GPUs. Supermicro claims
a 12 times performance boost compared to a traditional
quad-core CPU-based 1U server.
Petrobras, the leading Brazilian International Energy
company, recently spoke about its reliance on Tesla
GPUs to increase the performance of its seismic data
processing. Petrobras has invested in a GPU-based cluster
consisting of 190 NVIDIA Tesla GPUs.
“With our GPU cluster we are getting performance
improvements of 5x to 20x over our traditional multi-
core CPU-based cluster,” said Neiva Zago, Geophysical
Technology Manager, Petrobras. “We expect that
the continued use of GPUs in our business
will result in significant reduction
in processing time as well
as savings in power
consumption and
Fig. 5. Significant gains in performance of 3D seismic datacenter floor
analysis algorithms are achieved with the Multi-GPU space.”
enabled SVI Pro 2009. The graph shows initial bench- Petrobras expects
mark performance improvements measured for a scalable increases in
number of SVI Pro’s algorithms for noise cancellation, GPU performance
stratigraphic and structural analysis of 3D seismic data, will continue as it builds on its
using a modern multiple GPU system. Speed increases datacenter to Fig. 6. NVIDIA’s Tesla C1060 Graphics Processing
of up to 23x are seen on a single GPU and these stack deliver more than Unit (GPU) has 1 teraflop of processing power
up to a 37x increase when using 3 GPUs in parallel. 400 teraflops. l and 4GB memory.
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