Skip to Main Content
Designing Scientific Applications on GPUs
book

Designing Scientific Applications on GPUs

by Raphael Couturier
November 2013
Intermediate to advanced content levelIntermediate to advanced
498 pages
17h 6m
English
Chapman and Hall/CRC
Content preview from Designing Scientific Applications on GPUs
Linear programming on a GPU: a case study 235
E is merely the identity matrix having the `
th
column replaced by the vector
η. The update of the matrix B
1
can be rewritten as
ˆ
B
1
ij
= B
1
ij
1
d
i
d
`
, i 6= `,
ˆ
B
1
`j
=
B
1
`j
d
`
As shown in Listing 10.2, each block of the kernel processes a single column
while each thread may compute multiple elements of a column. This organi-
zation ensures that global memory accesses are coalescent since the matrix B
is stored column-wise.
Listing 10.2. basis update
extern s h a r e d v o l a t i l e double s da t a [ ] ;
g l o b a l void
u pd a t e B as i s K e r ne l ( in t m, u i n t l , double d l , double B,
u i n t pi
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Introduction to Numerical Analysis and Scientific Computing

Introduction to Numerical Analysis and Scientific Computing

Nabil Nassif, Dolly Khuwayri Fayyad
Computational Electromagnetism

Computational Electromagnetism

Alain Bossavit, Isaak D. Mayergoyz

Publisher Resources

ISBN: 9781466571648