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Graphical Processing Units (GPUs) have recently become a valuable computingtool for the acquisition of data at high rates and for a relatively low cost.The devices work by parallelizing the code into thousands of threads, eachexecuting a simple process, such as identifying pulses from a waveformdigitizer. The CUDA programming library can be used to effectively write codeto parallelize such tasks on Nvidia GPUs, providing a significant upgrade inperformance over CPU based acquisition systems.  The muon $g$-$2$ experiment at Fermilab is heavily relying on GPUs to processits data. The data acquisition system for this experiment must have the abilityto create deadtime-free records from 700 $\mu$s muon spills at a raw data rate18 GB per second. Data will be collected using 1296 channels of $\mu$TCA-based800 MSPS, 12 bit waveform digitizers and processed in a layered array ofnetworked commodity processors with 24 GPUs working in parallel to perform afast recording of the muon decays during the spill. The described dataacquisition system is currently being constructed, and will be fullyoperational before the start of the experiment in 2017.

Data Acquisition with GPUs: The DAQ for the Muon $g$-$2$ Experiment at Fermilab