DeepSparse v0.1.1 Patch Release

This is a patch release for 0.1.0 that contains the following changes:

• Docs updates: tagline, overview, update to use sparsification for verbiage
• Examples updated to use new ResNet-50 pruned_quant moderate model from the SparseZoo
• Nightly build dependencies now match on major.minor and not full version
• Benchmarking script added for reproducing ResNet-50 numbers
• Small (3-5%) performance improvement for pruned quantized ResNet-50 models, for batch size greater than 16
• Reduced memory footprint for networks with sparse fully connected layers
• Improved performance on multi-socket systems when batch size is larger than 1

DeepSparse v0.1.0 First GitHub Release

Welcome to our initial release on GitHub! Older release notes can be found here.

New Features:

• Operator support enabled:
  • QLinearAdd
  • 2D QLinearMatMul when the second operand is constant
• Multi-stream support added for concurrent requests.
• Examples for benchmarking, classification flows, detection flows, and Flask servers added.
• Jupyter Notebooks for classification and detection flows added.
• MakeFile flows and utilities implemented for GitHub repo structure.

Changes:

• Software packaging updated to reflect new GitHub distribution channel, from file naming conventions to license enforcement removal.
• Initial startup message updated with improved language.
• Distribution now manylinux2014 compliant; support for Ubuntu 16.04 deprecated.
• QuantizeLinear operations now use division instead of scaling by reciprocal for small quantization scales.
• Small performance improvements made on some quantized networks with nontrivial activation zero points.

Resolved Issues:

• Networks with sparse quantized convolutions and nontrivial activation zero points now have consistent correct results.
• Crash no longer occurs for some models where a quantized depthwise convolution follows a non-depthwise quantized convolution.

Known Issues:

• None