Experiment with OMP_NUM_THREADS=4, times in s, c5.12xlarge

|batchxchanne| New code | MKL      |
|    1x   32 | 0.0000288| 0.0000278|
|  128x   32 | 0.0000308| 0.0000311|
| 2560x   32 | 0.0000712| 0.0000672|
| 4096x   32 | 0.0000946| 0.0000910|
| 8192x   32 | 0.0001597| 0.0001523|
|16384x   32 | 0.0002905| 0.0002619|
|    1x   64 | 0.0000264| 0.0000256|
|  128x   64 | 0.0000339| 0.0000330|
| 2560x   64 | 0.0000829| 0.0000972|
| 4096x   64 | 0.0001137| 0.0001356|
| 8192x   64 | 0.0002027| 0.0002435|
|16384x   64 | 0.0003715| 0.0004639|
|    1x  128 | 0.0000262| 0.0000263|
|  128x  128 | 0.0000325| 0.0000389|
| 2560x  128 | 0.0001074| 0.0001580|
| 4096x  128 | 0.0001505| 0.0002336|
| 8192x  128 | 0.0002861| 0.0004481|
|16384x  128 | 0.0005648| 0.0008613|
|    1x  256 | 0.0000273| 0.0000276|
|  128x  256 | 0.0000390| 0.0000431|
| 2560x  256 | 0.0001533| 0.0002811|
| 4096x  256 | 0.0002258| 0.0004300|
| 8192x  256 | 0.0004300| 0.0008464|
|16384x  256 | 0.0010436| 0.0017613|
|    1x  512 | 0.0000256| 0.0000302|
|  128x  512 | 0.0000408| 0.0000551|
| 2560x  512 | 0.0002444| 0.0005225|
| 4096x  512 | 0.0003828| 0.0008147|
| 8192x  512 | 0.0008832| 0.0017192|
|16384x  512 | 0.0058463| 0.0074497|
|    1x  768 | 0.0000252| 0.0000308|
|  128x  768 | 0.0000450| 0.0000676|
| 2560x  768 | 0.0003440| 0.0007719|
| 4096x  768 | 0.0005890| 0.0013346|
| 8192x  768 | 0.0014946| 0.0026145|
|16384x  768 | 0.0089495| 0.0113557|
|    1x 1024 | 0.0000285| 0.0000308|
|  128x 1024 | 0.0000487| 0.0000786|
| 2560x 1024 | 0.0004614| 0.0010190|
| 4096x 1024 | 0.0008083| 0.0017376|
| 8192x 1024 | 0.0059020| 0.0075588|
|16384x 1024 | 0.0116553| 0.0146855|

Benchmark program
```python
import mxnet as mx
import time

def time_procedure(shape, count):
  data = mx.nd.random_uniform(shape=shape, low=-1.0, high = 1.0)
  factors = mx.nd.random_uniform(shape=(shape[-1],))
  mx.nd.waitall()
  begin = time.time()
  for i in range(0, count):
    out = mx.nd.LayerNorm(data, factors, factors)
    mx.nd.waitall()
  return (time.time() - begin) / count

count = 200

for channel in [32, 64, 128, 256, 512, 768, 1024]:
  for batch in [1, 128, 2560, 4096, 8192, 16384]:
    s = (batch, channel)
    timing = time_procedure(s, count)
    print("{:5d}x{:5d} | {:.7f}".format(s[0], s[1], timing))
```

…ust have signed integral type

… layernorm