Speeding up file carving using Graphical Processing Units
The recovery of forensic artefacts from digital media depends upon efficient search methods to process subject material. As harddrive capacity has continued to grow exponentially, with 2TB drives now becoming common, the weaknesses with the current search approaches and bus-bound architecture of current processors have become apparent.
Graphical Processing Units were initially designed to speed up the memory intensive processes of texture mapping, rendering polygons and geometric calculations; they can process matrix and vector calculations at a much higher rate than conventional CPUs, hence finding applications as diverse as molecular modelling and protein folding. GPUs can run huge numbers of threads in parallel with shared memory stacked on the processor, avoiding the data bus bottleneck of conventional processor architecture. Being capable of fast parallel computation through significant volumes of data they are a logical choice to speed up the search for, and recovery of, digital artefacts. However, they have a single instruction unit for multiple threads and using common binary search algorithms can result in poor performance. This research demonstrates that by implementing a state-based search the search time becomes linear with simple and, crucially, highly parallel kernel code on the GPU and significantly shorter search times.
Benjamin Donnachie & SEAN TOHILL
School of Electronics and Computer Science, University of Westminster
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