Add vtr-optimized, with PGO enabled.

[HackerFoo]

This PR adds a version of VTR that is optimized using profile-guided optimization, which reduces runtime by ~8%.

To do this, it must download a sample architecture and circuit, and run all steps to gather profile data, and then recompile using the profile data collected.

This PR supersedes SymbiFlow/conda-packages#143

[PiotrZierhoffer]

I restarted the failing jobs (there was a problem with github connection), but from the packaging perspective - lgtm.

I am not sure if @litghost ACKs these changes as well or is there still something to be fixed?

[PiotrZierhoffer]

If you let me know it's good to go I'll merge right away

[litghost]

LGTM, merge if green. Would also be good to get some concrete % improvement numbers.

[litghost]

Looks like an ibex workaround file was left in the build.sh?

[HackerFoo]

Looks like an ibex workaround file was left in the build.sh?

I've removed it.

[litghost]

Error https://travis-ci.com/github/litex-hub/litex-conda-eda/jobs/460723313#L1245:

  File "/home/travis/build/litex-hub/litex-conda-eda/workdir/conda-env/lib/python3.7/site-packages/conda/resolve.py", line 288, in verify_specs
    raise ResolvePackageNotFound(bad_deps)
.
  - python-constraint

The key here is that you want to do a pip install, not install a conda package. Example: https://github.com/SymbiFlow/symbiflow-arch-defs/blob/442941d382bdbe212c1a9b153e2c623aa2fd707d/environment.yml#L29
You can also include a requirements.txt, example: https://github.com/SymbiFlow/symbiflow-arch-defs/blob/7183cb5e59d50955686c12e4b800a55fafd1fae5/environment.yml#L24-L26

[HackerFoo]

ValueError: Dictionaries are not supported as values in requirements sections. Note that pip requirements as used in conda-env environment.yml files are not supported by conda-build.

I guess I need to use the Conda version.

[HackerFoo]

LGTM, merge if green. Would also be good to get some concrete % improvement numbers.

For minilitex_ddr_arty:

Phase	vtr	vtr-optimized	Improvement
fasm	32.2	28.0	13%
pack	99.7	97.2	2.5%
place	49.3	43.0	12%
route	108	84.9	22%
TOTAL	289	253	13%