From bb19bf5a49e1c31cd28258aa69b1f7e083096caa Mon Sep 17 00:00:00 2001 From: Georg Hager Date: Thu, 14 Mar 2019 12:07:14 +0100 Subject: [PATCH] Update README.md --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 0c43294..72fc4c3 100644 --- a/README.md +++ b/README.md @@ -9,10 +9,10 @@ It contains the following streaming kernels with corresponding data access patte * sum (L1): Vector reduction: `s += a`. Load only. * copy (L1, S1, WA): Classic memcopy: `a = b`. * update (L1, S1): Update vector: `a = a * scalar`. Also load + store but without write allocate. -* triad (L2, S1, WA): Stream triad - `a = b + c * scalar`. -* daxpy (L2, S1): Daxpy - `a = a + b * scalar`. -* striad (L3, S1, WA): Schoenauer triad - `a = b + c * d`. -* sdaxpy (L3, S1): Schoenauer triad without write allocate - `a = a + b * c`. +* triad (L2, S1, WA): Stream triad: `a = b + c * scalar`. +* daxpy (L2, S1): Daxpy: `a = a + b * scalar`. +* striad (L3, S1, WA): Schoenauer triad: `a = b + c * d`. +* sdaxpy (L3, S1): Schoenauer triad without write allocate: `a = a + b * c`. As added benefit the code is a blueprint for a minimal benchmarking application with a generic makefile and modules for aligned array allocation, accurate timing and affinity settings. Those components can be used standalone in your own project.