remove caveats of draft version, fix a few minor items

lanl · Aug 28, 2024 · 916efcb · 916efcb
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diff --git a/doc/sphinx/00_intro/SSNI-baseline.xlsx b/doc/sphinx/00_intro/SSNI-baseline.xlsx
diff --git a/doc/sphinx/00_intro/introduction.rst b/doc/sphinx/00_intro/introduction.rst
@@ -294,9 +294,9 @@ Note:  % of device memory is approximate please note actual memory footprint use
 SSNI Baseline
 ===================================
 
-The SSNI Baseline spreadsheet linked below provides draft FOMs and example calculations of FOMs for two hypothetical systems with different primary node types and a third hypothetical system with a secondary node type using a subset of the SSNI benchmarks.
+The SSNI Baseline spreadsheet linked below provides FOMs and example calculations of FOMs for two hypothetical systems with different primary node types and a third hypothetical system with a secondary node type using a subset of the SSNI benchmarks.
 
-:download:`SSNI-baseline-draft-v2.xlsx <SSNI-baseline-draft-v2.xlsx>`
+:download:`SSNI-baseline.xlsx <SSNI-baseline.xlsx>`
 
 
 System Information

diff --git a/doc/sphinx/05_mlmd/mlmd.rst b/doc/sphinx/05_mlmd/mlmd.rst
@@ -261,10 +261,10 @@ Results from MLMD are provided on the following systems:
 
 Training HIPNN Model
 --------------------
-For the training task, only a single FOM needs to be reported, the average epoch time found in the ``model_results.txt`` file. 
+For the training task, only a single FOM needs to be reported, the 1 / average epoch time found in the ``model_results.txt`` file. 
 
-* On Chicoma using a single GPU - 1 / FOM Average Epoch time:  1/0.24505662 = 4.05709
-* On Crossroads using a single node - 1 / FOM Average Epoch time:   1/1.67033911= .5986808
+* On Chicoma using a single GPU - 1 / Average Epoch time:  1/0.24505662 = 4.05709
+* On Crossroads using a single node - 1 /  Average Epoch time:   1/1.67033911= .5986808
 
 Simulation+Inference 
 --------------------

diff --git a/doc/sphinx/06_umt/umt.rst b/doc/sphinx/06_umt/umt.rst
@@ -23,7 +23,7 @@ The benchmark problem is a single node sweep performance problem (SPP) on a 3D u
 - SPP 1, a configuration with a high number of unknowns per spatial element with 72 directions and 128 energy bins to solve per
   mesh cell.
 - SPP 2, a configuration with a low number of unknowns per spatial element with 32 directions and 16 energy bins to solve per mesh
-  cell.  SPP 2 is still a work in progress.
+  cell.
 
 
 Figure of Merit