From: lkcl <lkcl@web>
Date: Wed, 20 Apr 2022 16:11:26 +0000 (+0100)
Subject: (no commit message)
X-Git-Tag: opf_rfc_ls005_v1~2677
X-Git-Url: https://git.libre-soc.org/?a=commitdiff_plain;h=d49a8cbae8b13ecf7f94c7569015ce1914e24fcf;p=libreriscv.git

---

diff --git a/openpower/sv/biginteger.mdwn b/openpower/sv/biginteger.mdwn
index 1a26cfafb..fd26967ea 100644
--- a/openpower/sv/biginteger.mdwn
+++ b/openpower/sv/biginteger.mdwn
@@ -147,7 +147,7 @@ vector. Overall it is extremely powerful.
 The simplest implementation of big-int divide is the standard schoolbook
 "Long Division", set with RADIX 64 instead of Base 10. Donald Knuth's
 Algorithm D performs estimates which, if wrong, are compensated for
-afterwards.  Essentiallythere are three phases:
+afterwards.  Essentially there are three phases:
 
 * Calculation of the quotient estimate. This is Scalar division
   and can be ignored for the scope of this analysis
@@ -156,7 +156,11 @@ afterwards.  Essentiallythere are three phases:
   phase 1 was wrong by one digit.
 
 In essence then the primary focus of Vectorised Big-Int divide is in
-fact big-integer multiply (or, mul-and-subtract).
+fact big-integer multiply (more specifically, mul-and-subtract).
+
+    product = RC - (RA) * (RB)
+    RT = lowerhalf(product)
+    RS = upperhalf(product)
 
 # Appendix