May 18, 2014

nnForge v1.1.5

I ported performance improvemetns for forward propagation of convolutional layers in GPU backend to hessian calculators and weight updaters. Get latest release of nnForge v1.1.5:
  • Performance of weight updaters for convolutional layers is improved in CUDA backend. Mostly for Kepler architecture. The increase is much smaller than for forward prop, I got >800 GFLOPs on training single Galaxy Zoo network on GeForce Titan
  • Convolutional 1D, 2D, 3D, and 4D layers are fully supported by CUDA backend (it was 2D and 3D only before)
  • Fixed training multiple networks with CPU backend
  • Fixed supervised_data_mem_reader for float input data

No comments:

Post a Comment