Lecture Notes in Computer Science 4917

Drug Design Issues on the Cell BE 187
6.3 Parallelization Using the Two Cell BE of the Blade
So far, we have presented FTDock execution time results using several SPEs on
the same Cell BE processor of a Cell BE Blade. In this section we present results
for the MPI FTDock parallelization using the two Cell BE of a Blade.
Figure 7 shows the total execution time using 1 or 2 MPI tasks (1 task on
1 PPE), and 1, 2, 4 and 8 SPEs per task, for 128 3 (left) and 256 3 (right) grid
sizes. Using 1 task with n SPEs is slower (less efficient) than using 2 tasks with
n/2 SPEs. The main reason is that we distribute the contention of the EIB and
the main memory between the two Cell BEs of a Blade. Actually, that can be
seen comparing the execution time of 1 task and 2 tasks for the same number of
SPEs; execution time is not divided by two.
seconds
150
100
50
0
1 MPI
2 MPIs
1 2 4 8
SPEs
a) 128 3 grid size
seconds
1500
1000
500
0
1 MPI
2 MPIs
1 2 4 8
SPEs
b) 256 3 grid size
Fig. 7. Total execution time of the parallel implementation of FTDock using 1 or 2
MPI tasks and 1, 2, 4 and 8 SPEs/task, for 128 3 (left), and 256 3 (right) grid sizes
6.4 Parallelization Using Dual-Thread PPU Feature
The PPE hardware supports two simultaneous threads of execution [2], duplicating
architecture and special purpose registers, except for some system-level
resources such as memory.
Discretize function accesses a working data set that perfectly fits in second
level of cache. Indeed, the discretize function has a lot of branches that
may not be predicted by the PPE branch-prediction hardware. Hence, a second
thread may make forward progress and increase PPE pipeline use and system
throughput. We achieve 1.5x of the Discretize function when parallelizing it using
OpenMP, and a 1.1 − 1.2x overall improvement of the FTDock application.
In any case, function offloading and vectorization of that function would get
better performance improvements and scalability.
7 Comparison with a POWER5 Multicore Platform
In this section we compare our Cell BE implementation of the FTDock with
a parallel version of the FTDock, running on a POWER5 multicore with two