Copy in exponentially-increasing sized chunks when performing array repeat.  This enables fast initialization of large arrays.  Performance is about an order of magnitude increase for single-element arrays, and about two orders of magnitude faster for single-element character arrays (see comments)

Benchmarks on slightly-contended machine; before & after

[ python-trunk]$ python -m timeit -s "from array import array" "array('c', '\0')*100000"
100 loops, best of 3: 4 msec per loop
[ python-trunk]$ ./python -m timeit -s "from array import array" "array('c', '\0')*100000"
100000 loops, best of 3: 14.5 usec per loop

[ python-trunk]$ python -m timeit -s "from array import array" "array('i', [0])*100000"
100 loops, best of 3: 3.42 msec per loop
[ python-trunk]$ ./python -m timeit -s "from array import array" "array('i', [0])*100000" 
1000 loops, best of 3: 517 usec per loop

[ python-trunk]$ python -m timeit -s "from array import array" "array('i', [0,1,2,3])*100000"
100 loops, best of 3: 4.95 msec per loop
[ python-trunk]$ ./python -m timeit -s "from array import array" "array('i', [0,1,2,3])*100000"
100 loops, best of 3: 2.55 msec per loop

[ python-trunk]$ python -m timeit -s "from array import array" "array('c', '\0'*100)*1000"
10000 loops, best of 3: 46.6 usec per loop
[ python-trunk]$ ./python -m timeit -s "from array import array" "array('c', '\0'*100)*1000"
100000 loops, best of 3: 19.6 usec per loop

[ python-trunk]$ python -m timeit -s "from array import array" "array('c', '\0'*1000)*100"
10000 loops, best of 3: 22.8 usec per loop
[ python-trunk]$ ./python -m timeit -s "from array import array" "array('c', '\0'*1000)*100"
10000 loops, best of 3: 20.7 usec per loop

How does this patch relate to patch #1569291?

The patches have virtually identical functionality and performance characteristics.