installation proofreading, split parallel compilation

diff --git a/docs/installation.md b/docs/installation.md
index db9f677..02423a2 100644 (file)
--- a/docs/installation.md
+++ b/docs/installation.md
@@ -47,9 +47,9 @@ You will also need other packages, most of which can be installed via apt-get us
 
 On CentOS or RHEL, you can install via yum using:
 
-    sudo yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel 
+    sudo yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel
 
-The only exception being the google logging library, which does not exist in the Ubuntu 12.04 or CentOS/RHEL repository. To install it, do:
+The only exception being the google logging library, which does not exist in the Ubuntu 12.04 or CentOS/RHEL repositories. To install it, do:
 
     wget https://google-glog.googlecode.com/files/glog-0.3.3.tar.gz
     tar zxvf glog-0.3.3.tar.gz
@@ -66,11 +66,13 @@ After setting all the prerequisites, you should modify the `Makefile.config` fil
 
 ## Compilation
 
-After installing the prerequisites, simply do `make all -j10` in which 10 is the number of parallel compilation threads to compile Caffe. If you would like to compile the Python and Matlab wrappers, do
+After installing the prerequisites, simply do `make all` to compile Caffe. If you would like to compile the Python and Matlab wrappers, do
 
     make pycaffe
     make matcaffe
 
+For a faster build, compile in parallel by doing `make all -j8` where 8 is the number of parallel threads for compilation. A good choice for the number of threads is the number of cores in your machine.
+
 Optionally, you can run `make distribute` to create a `distribute` directory that contains all the necessary files, including the headers, compiled shared libraries, and binary files that you can distribute over different machines.
 
 To use Caffe with python, you will need to add `/path/to/caffe/python` or `/path/to/caffe/build/python` to your `PYTHONPATH`.