Parallel Programming: for Multicore and Cluster Systems- P31 docx
Parallel Programming: for Multicore and Cluster Systems- P31 docx
... call removes the most recently added handler from the cleanup stack. For
execute=0, this handler will be executed when it is removed. For execute=0,
this handler will be removed without execution. ... cancelled while waiting for the
condition variable ps->cond. In this case, the thread first becomes the owner of the
mutex variable before termination. Therefore, a cleanup handler is u...
Parallel Programming: for Multicore and Cluster Systems- P31 potx
... call removes the most recently added handler from the cleanup stack. For
execute=0, this handler will be executed when it is removed. For execute=0,
this handler will be removed without execution. ... used as cleanup handler and arg spec-
ifies the corresponding argument values. The cleanup handlers on the cleanup stack
are organized in LIFO (last-in, first-out) order, i.e., the handlers...
Parallel Programming: for Multicore and Cluster Systems- P12 docx
... used for
distributed address space. The fork–join concept is, for example, used in OpenMP
for the creation of threads executing a parallel loop, see Sect. 6.3 for more details.
The spawn and exit ... t1 and t2 are temporary array variables.
More information on parallel loops and their execution as well as on transforma-
tions to improve parallel execution can be found in...
Parallel Programming: for Multicore and Cluster Systems- P23 docx
... the case for point-to-point operations. The main reason
for this is to avoid a large number of additional MPI functions. For the same rea-
son, only the standard modus is supported for collective ... array aout and the corresponding process ranks are stored in array
ind. For the collection of the information based on value pairs, a data structure is
defined for the elements of ar...
Parallel Programming: for Multicore and Cluster Systems- P24 docx
... of the p processes and therefore lies between 0 and p −1.
For a correct execution, each participating process must provide for each other
process data blocks of the same size and must also receive ... useful for the implementation
of task -parallel programs and are the basis for the communication mechanism
of MPI.
In many situations, it is useful to partition the processes ex...
Parallel Programming: for Multicore and Cluster Systems- P28 docx
... use a different order for locking the mutex variables. This
can be seen for two threads T
1
and T
2
and two mutex variables ma and mb as
follows:
• thread T
1
first locks ma and then mb;
• thread ... priorities and the scheduling strategies used, see Sect. 6.1.9 for more
information. The order in which waiting threads become owner of a mutex variable
is not defined in the Pthrea...
Parallel Programming: for Multicore and Cluster Systems- P41 docx
... effort which is needed for banded matrices with a dense band
of semi-bandwidth N. In the following, we consider the method of cyclic reduction
for banded matrices, which preserves the sparse banded ... Illustration of the parallel algorithm for the cyclic reduction for n = 8 equations and
p = 2 processors. Each of the processors is responsible for q = 4 equations; we have Q = 2....
Parallel Programming: for Multicore and Cluster Systems- P43 docx
... F
00
·
x
(k)
R
x
(k)
B
+ω
b
1
b
2
.
For a parallel implementation the component form of this system is used. On
the other hand, for the convergence results the matrix form and the iteration matrix
have ... R
n
R
×n
R
, D
B
∈ R
n
B
×n
B
, E ∈ R
n
B
×n
R
, and F ∈ R
n
R
×n
B
.
The submatrices D
R
and D
B
are diagonal matrices and the submatrices E and F
are sparse band...
Parallel Programming: for Multicore and Cluster Systems- P18 docx
... be
performed in three time steps.
4.2 Performance Metrics for Parallel Programs 165
4.2.2 Scalability of Parallel Programs
The scalability of a parallel program captures the performance behavior for ... cannot be
implemented faster and the time Θ(p) results.
4.2 Performance Metrics for Parallel Programs 163
new sequential algorithm performs p times more steps than the paralle...
Parallel Programming: for Multicore and Cluster Systems- P21 docx
... Language bindings for C, C++, Fortran-77, and Fortran-95 are sup-
ported. In the following, we concentrate on the interface for C and describe the
most important features. For a detailed description, ... 2
Compute the resulting MIPS rate for program X.
Exercise 4.3 There is a SPEC benchmark suite MPI2007 for evaluating the MPI
performance of parallel systems for floating-poin...
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