Change wording ...

paper.tex

@@ -116,12 +116,14 @@ developed a high-performance DMA engine based on Xilinx's PCIe Gen3 Core.To
 process the data, we encapsulated the DMA setup and memory mapping in a plugin
 for our scalable GPU processing framework~\cite{vogelgesang2012ufo}. This
 framework allows for an easy construction of streamed data processing on
-heterogeneous multi-GPU systems. The framework is based on OpenCL,  and
+heterogeneous multi-GPU systems. Because the framework is based on OpenCL,
 integration with NVIDIA's CUDA functions for GPUDirect technology is not
-possible. We therefore integrated direct FPGA-to-GPU communication into our
-processing pipeline using AMD's DirectGMA technology. In this paper we report
-the performance of our DMA engine for FPGA-to-CPU communication and some
-preliminary measurements about DirectGMA's performance in low-latency applications.
+possible at the moment. Thus, we used AMD's DirectGMA technology to integrate
+direct FPGA-to-GPU communication into our processing pipeline. In this paper we
+report the performance of our DMA engine for FPGA-to-CPU communication and some
+preliminary measurements about DirectGMA's performance in low-latency
+applications.
+
 
 \section{Architecture}
 
@@ -143,7 +145,7 @@ they are not directly involved in the data transfer anymore.
     In a traditional DMA architecture (a), data are first written to the main
     system memory and then sent to the GPUs for final processing.  By using
     GPUDirect/DirectGMA technology (b), the DMA engine has direct access to
-    GPU's internal memory.
+    the GPU's internal memory.
   }
   \label{fig:trad-vs-dgpu}
 \end{figure}