benjaminPKP

4 ms·

1. 1.▲
   by benjaminPKP 10y ago

   Oh wow. Now that's embarrassing. My bad for stirring things up with that
2. 2.▲
   by benjaminPKP 10y ago

   It's actually about 75x faster, not 1000x. I mean there's a difference between parallelizing basic code vs something like the LeNet-5. The sequential code was pretty standard. I mean I'm sure the CPU code could've been o
3. 3.▲
   by benjaminPKP 10y ago

   It was run on a tesla k80 cluster, so pretty high end. But the reason we were able to get such acceleration is because we wrote the the low-end CUDA code, using as much register memory and shared memory as possible, while using good streami
4. 4.▲
   by benjaminPKP 10y ago

   We implemented the LeNet-5 convolutional neural network, and yes when run sequentially it really does take that long. The sequential code that took that long was also written by professors who worked at NVIDIA, it was written as well as it
5. 5.▲
   by benjaminPKP 10y ago

   Just took an applied parallel programming class at a top 5 engineering school. The untapped potential for GPUs really is crazy. If GPUs could be used for common tasks able to be parallelized, then less work for the CPU and way quicker compu