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updated notes on Ubuntu llvm versions (#3769)

Summary:
updated notes on Ubuntu llvm version ship inclusions and requirements.

Documentation:

[Optional Fixes #issue]
Pull Request resolved: #3769

Test Plan: Please see a detailed explanation of how to fill out the fields in the relevant sections in PULL_REQUEST.md.

Differential Revision: D18688899

Pulled By: jfix71

fbshipit-source-id: e4119899d94948c38563cdaf8938af9a2a423d6f
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badenh authored and facebook-github-bot committed Dec 10, 2019
1 parent 0dd4ae2 commit fad7bc073ea2ed78e78b0d1b6f3959c03a92d227
Showing with 3 additions and 4 deletions.
  1. +2 −3 README.md
  2. +1 −1 tests/unittests/RecommendationSystemTest.cpp
@@ -116,7 +116,7 @@ For MacPorts, run:
#### Ubuntu

[The following instructions have been tested on Ubuntu 16.04]
[The following instructions have been tested on Ubuntu 16.04 and 18.04]

In order to build Glow on Ubuntu it is necessary to install a few packages. The
following command should install the required dependencies:
@@ -126,8 +126,7 @@ following command should install the required dependencies:
libprotobuf-dev llvm-8 llvm-8-dev ninja-build protobuf-compiler wget \
opencl-headers libgoogle-glog-dev
```
[Note: building Glow on Ubuntu 16.04 with llvm-7 fails because llvm-7 xenial distribution
uses an older c++ ABI]
[Note: Ubuntu 16.04 and 18.04 ship with llvm-6 and need to be upgraded before building Glow. Building Glow on Ubuntu 16.04 with llvm-7 fails because llvm-7 xenial distribution uses an older c++ ABI, however building Glow on Ubuntu 18.04 with llvm-7 has been tested and is successful]

It may be desirable to use `update-alternatives` to manage the version of
clang/clang++:
@@ -161,7 +161,7 @@ static size_t sumOfElements(Handle<int32_t> H) {
/// * An initial Multilayer Perceptron acting in the inputs.
/// * Some number of Sparse Features: SparseLengthSum nodes acting on
/// embedding tables (see https://caffe2.ai/docs/sparse-operations.html).
/// * An interaction layer bringing together the output for hte top MLP and
/// * An interaction layer bringing together the output for the top MLP and
/// the sparse features.
/// * A final MLP acting on the result of the interaction.
///

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