Assuming that all variables are of integral or floating point types, there is absolutely no sense to parallelize this code (in the sense of executing by different threads/cores), as the overhead will be much much higher than any benefit out of it. The applicable parallelism in this example is at the level of multiple computation units and/or vectorization on a single CPU. Optimizing compilers are sophisticated enough nowadays to exploit this automatically, without code changes; however if you wish you may explicitly use temporary variables, as in the second part of the question.
And if you ask just out of curiosity: Intel Parallel Studio provides several ways to parallelize code. For example, let's use Cilk keywords together with C++11 lambda functions:
#include <cilk/cilk.h>
...
temp = cilk_spawn [=]{ return a+b; }();
sum = c+d;
cilk_sync;
sum += temp;
Don't expect to get performance out of that (see above), unless you use classes with a computational-heavy overloaded operator+
.