Nicolo's updates
- Edge SpAIce Gitlab Pipeline:
- 4 stages implemented:
- check: test if the commit come from
edge-spaice
branch, otherwise abort the execution of the pipeline
- fetch: retrieve QONNX models from the submodule
edge-spaice-models
which have to be tested in the pipeline. Generated QONNX channels-first models as artifacts.
- convert: transform the QONNX models in channels-last format and check whether the modification creates any numerical mismatch. Generate QONNX channels-last models as artifacts.
- generate: produce hls4ml models from the QONNX channels-last models, check whether there are mismatches between hls4ml and QONNX predictions. Generate some images as artifacts
- The pipeline is triggered everytime that:
github.com/nghielme/hls4ml@edge-spaice
receive a push
github.com/nghielme/QONNX@edge-spaice
receive a push
gitlab.cern.ch/edge-spaice/edge-spaice-pipeline@master
receive a push
gitlab.cern.ch/edge-spaice/edge-spaice-models@master
receive a push
- Nicolas has now access to the pipeline and can push the new models directly into
edge-spaice-models
- To be implemented:
- Execute the pipeline in parallel for each fetched model:
parallel:matrix
require an array of string for the parameters, no evaluation can be executed before running the pipeline
- Add
build
stage in which the hls4ml generated model is built using vitis_hls
and vivado
- Idea to discuss: profile the weights and avoid to repeat the same values multiple times across different layers.
For example,
- with 4 bits only 25 - 1 = 31 different values can exist
- with 8 bits, 29 - 1 = 511
Each layer uses pointers to a central common storage of ap_fixed<>
values to represent the weights, and need to know the scale of the value
Stelios' Updates
- Vladimir to review the open PRs soon
- Conferences->check shared codimd
- Gitlab wikis in progress
- PixESL
- meeting on Thursday
- Need ROOT to get the clustered data
- presentation