performance gain ith ACL #2

I did performance profiling on classification with BVLC model between original caffe and caffeonacl and saw some gain, but as big as I am hoping. Is this also what you observe on your platform?
I use the following command on firefly 3399:

./build/examples/cpp_classification/classification.bin models/bvlc_reference_caffenet/deploy.prototxt models/bvlc_reference_caffene
t/bvlc_reference_caffenet.caffemodel data/ilsvrc12/imagenet_mean.binaryproto data/ilsvrc12/synset_words.txt examples/images/cat.jpg

and measure time spent below:

std::vector Classifier::Classify(const cv::Mat& img, int N) {
std::vector output = Predict(img);
std::clock_t begin = std::clock();
output = Predict(img);

N = std::min(labels_.size(), N);
std::vector maxN = Argmax(output, N);
std::vector predictions;
for (int i = 0; i < N; ++i) {
int idx = maxN[i];
predictions.push_back(std::make_pair(labels_[idx], output[idx]));
}
std::clock_t end = std::clock();
double elapsed_secs = double(end - begin) / CLOCKS_PER_SEC;
std::cout <<"Time spent: " << elapsed_secs <<std::endl;

return predictions;
}

The time measurement for Caffe and CaffeOnACL are below:

CaffeonACL
Time spent: 4.53536
0.3134 - "n02123045 tabby, tabby cat"
0.2380 - "n02123159 tiger cat"
0.1235 - "n02124075 Egyptian cat"
0.1003 - "n02119022 red fox, Vulpes vulpes"
0.0715 - "n02127052 lynx, catamount"

Original Caffe
Time spent: 5.5306
0.3134 - "n02123045 tabby, tabby cat"
0.2380 - "n02123159 tiger cat"
0.1235 - "n02124075 Egyptian cat"
0.1003 - "n02119022 red fox, Vulpes vulpes"
0.0715 - "n02127052 lynx, catamount"