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DistribComputing/README.md

@@ -28,9 +28,9 @@ elapsed time: 31.756677491 seconds (8232411136 bytes allocated)
 
 **Submit** the line starting with ``elapsed time``. The profiler in Julia works by taking a sample every millisecond and recording which line of code is currently being executed. For example, the first line of the output means that in 5,656 of the samples (5.6 seconds), Julia was executing ``f`` at line 4 of gradient.jl. Which lines of code are dominating the execution time?
 
-**Challenge**: Try to make the code run twice as fast. Some possible approaches include reusing calculations and avoiding temporary objects. Feel free to restructure the code or implement your own version. Submit your new solution and execution time. Don't spend too much time on this. **[Suggested reading]**
+**Challenge**: Try to make the code run twice as fast. Some possible approaches include reusing calculations and memory instead of computing ``Q*x`` multiple times and creating new vectors on each iteration. Feel free to restructure the code or implement your own version. Submit your new solution and execution time. Don't spend too much time on this; we will work on this example in the class. **[Suggested reading]**
 
-If you would like to follow along with the parallel computing example in class, run the ``data.R`` script in this directory. It will take a few minutes to run and will generate a ``tripsbydate`` subdirectory with a large number of files called, for example ``2011-10-12.csv.gz``. No submission is necessary.
+If you would like to follow along with the parallel computing example in class, run the ``data.R`` script in this directory. It will take a few minutes to run and will generate a ``tripsbydate`` subdirectory with a large number of files called, for example, ``2011-10-12.csv.gz``. No submission is necessary.
 
 [gradient.jl]: https://github.com/IainNZ/ORSoftwareTools2014/blob/master/DistribComputing/performance/gradient.jl
 [gradient descent]: http://en.wikipedia.org/wiki/Gradient_descent