(no commit message)

diff --git a/openpower/sv/biginteger/analysis.mdwn b/openpower/sv/biginteger/analysis.mdwn
index bda0ced551cbace44e2bc82bc80329ebe23a434d..bcaa0cd26c5d9344bde7aa76a06e34f016e4017c 100644 (file)
--- a/openpower/sv/biginteger/analysis.mdwn
+++ b/openpower/sv/biginteger/analysis.mdwn
@@ -3,8 +3,8 @@
 **DRAFT SVP64**
 
 * Revision 0.0: 21apr2022 <https://www.youtube.com/watch?v=8hrIG7-E77o>
-* Revision 0.1: 22apr2022 removal of msubed because sv.madded and sv.subfe works
-* Revision 0.2: 22apr2022 128/64 scalar divide, investigate Goldschmidt
+* Revision 0.01: 22apr2022 removal of msubed because sv.madded and sv.subfe works
+* Revision 0.02: 22apr2022 128/64 scalar divide, investigate Goldschmidt
 
 This page covers an analysis of big integer operations, to
 work out optimal Scalar Instructions to propose be submitted to
@@ -363,4 +363,5 @@ to 1-bit per loop, a simple compare, shift, and subtract).  If the simplest
 approach were deployed then the completion time for the 128/64 scalar
 divide would be a whopping 128 cycles.  To be workable an alternative
 algorithm is required, and one of the fastest appears to be
-Goldschmidt Division.
+Goldschmidt Division.  Whilst typically deployed for Floating Point,
+there is no reason why it should not be adapted to Fixed Point.