1 06/09/2011, COSMO GM Xavier Lapillonne
Porting the physical parametrizations on GPU using directives
X. Lapillonne, O. Fuhrer
Eidgenössisches Departement des Innern EDIBundesamt für Meteorologie und Klimatologie MeteoSchweiz
2 06/09/2011, COSMO GM Xavier Lapillonne
Outline
• Physics with 2d data structure
• Porting the physical parametrization to GPU using directives
• Running COSMO on an hybrid GPU-CPU system
3 06/09/2011, COSMO GM Xavier Lapillonne
New data structure
• 2D data fields inside the physics packages with one horizontal and one vertical dimensions: f(nproma,ke), with nproma = ie x je / nblock.
• Goals:• Physics package could be shared with ICON code• Blocking strategy: all physics parametrization could be computed
while data remains in the cache• organize_physics should be structured as follow:
call init_radiationcall init_turbulence …
do ib=1,nblockcall copy_to blockcall organize_radiation…call organize_turbulencecall copy_back
end do
• Note : an omp parallelization could be introduced around the block loop
where data inside organise_scheme is in block form t_b(nproma,ke)
Routines below organize_scheme will be shared with ICON. Fields are passed via argument list:
call fesft(t_b(:,:), …
4 06/09/2011, COSMO GM Xavier Lapillonne
Current status• Base code: COSMO 4.18
• 2d version of microphysics (hydci_pp), radiation (Ritter-Geleyn), turbulence (turbtran+turbdiff).
• For the moment microphysics and radiation are in separate block loop. The turbulence scheme is copying 3d fields (i.e turbdiff(t(:,je,:) …)
Next steps
• All 3 parametrizations (microphysics + radiation + turbulence) in a common block loop
• Performance analysis
• OMP parallelization (?)
Longer term
• All parametrization required for operational runs should be inside the block loop and in 2 dimensional form
5 06/09/2011, COSMO GM Xavier Lapillonne
Outline
• Physics with 2d data structure
• Porting the physical parametrization to GPU using directives
• Running COSMO on an hybrid GPU-CPU system
6 06/09/2011, COSMO GM Xavier Lapillonne
Computing on Graphical Processing Units (GPUs)
• Benefit from the highly parallel architecture of GPUs
• Higher peak performance at lower cost / power consumption.
• High memory bandwidth
CoresFreq.
(GHz)
Peak Perf.
S.P. (GFLOPs)
Peak Perf.
D.P. (GFLOPs)
Memory Bandwith (GB/sec)
Power
Cons. (W)
CPU: AMD
Magny-cours12 2.1 202 101 42.7 115
GPU: Fermi
M2050448 1.15 1030 515 144 225
7 06/09/2011, COSMO GM Xavier Lapillonne
Execution model
Host
(CPU)
Kernel
Sequential
Sequential
Device(GPU)
Data
Transfer
• Copy data from CPU to GPU(CPU and GPU memory are separate)
• Load specific GPU program (Kernel)
• Execution: Same kernel is executed by all threads, SIMD parallelism (Single instruction, multiple data)
• Copy back data from GPU to CPU
… …
… …
Parallel threads
8 06/09/2011, COSMO GM Xavier Lapillonne
The directive approach, an example
!$acc data region local(a,b)!$acc update device(b) !initialization !$acc region do k=1,nlev do i=1,N a(i,k)=0.0D0 end do end do !$acc end region
! first layer !$acc region do i=1,N a(i,1)=0.1D0 end do !$acc end region
! vertical computation !$acc region do k=2,nlev do i=1,N a(i,k)=0.95D0*a(i,k-1)+exp(-2*a(i,k)**2)*b(i,k) end do end do !$acc end region !$acc update host(a)!$acc end data region
!$acc data region local(a,b)!$acc update device(b) !initialization !$acc region do kernel do i=1,N do k=1,nlev a(i,k)=0.0D0 end do end do !$acc end region
! first layer !$acc region do i=1,N a(i,1)=0.1D0 end do !$acc end region
! vertical computation !$acc region do kernel do i=1,N do k=2,nlev a(i,k)=0.95D0*a(i,k-1)+exp(-2*a(i,k)**2)*b(i,k) end do end do !$acc end region !$acc update host(a)!$acc end data region
N=1000, nlev=60: t= 555 μs t= 225 μs
note : PGI directives
Loop reordering
3 different kernels
Array “a” remains on the GPU between the different kernel calls
9 06/09/2011, COSMO GM Xavier Lapillonne
Physical parametrizations on GPU using directives
• Physical parametrizations are tested using standalone code.
• Currently ported parametrizations:• PGI : microphysics (hydci_pp), radiation (fesft), turbulence (only
turbdiff yet)• OMP – acc (Cray) : microphysics, radiation • GPU optimizaiton: loop reordering, replacement of arrays with
scalars• Note: hydci_pp, fesft and turbdiff subroutines represents
respectively 6.7%, 8% and 7.3% of the total execution time of a typical cosmo-2 run.
• Current version of OMP-acc are a subset of PGI directives and it is possible to write PGI code so that there is almost a one to one translation to omp-acc.
• First investigation show similar performance between the two compilers, but would need further analysis
10 06/09/2011, COSMO GM Xavier Lapillonne
Results, Fermi card using PGI directives
Performance
0
5
10
15
20
25
30
microphysics radiation turbulence
GF
lop/
s
• Peak performance of a Fermi card for double precision is 515 GFlop/s, i.e. we are getting respectively 5%, 4.5% and 2.5% peak performance for the microphysics, radiation and turbulence schemes
• Theoretical bandwith is 140 GB/s, but maximum achievable is around 110 GB/s
• Test domain: nx x ny x nz = 80 x 60 x 60
Memory
0
20
40
60
80
100
120
microphysics radiation turbulence
Me
m.
Th
rou
gh
pu
t o
vera
ll (G
B/s
)
11 06/09/2011, COSMO GM Xavier Lapillonne
Results: Comparison with CPU
Speed up with respect to a 12 cores CPU (Palu)
0.000
1.000
2.000
3.000
4.000
5.000
6.000
7.000
Microphysics Radiation Turbulence
Sp
ee
d u
p execution time
execution + data transfer
• Parallel CPU code run on 12 cores AMD magny-cours CPU – however there are no mpi-communications in these standalone test codes.
• Note: Expected performance would be between 3x and 5x and depending whether the problem is compute or memory bandwith bound.
• Overhead of data transfer for microphysics and turbulence is very large.
12 06/09/2011, COSMO GM Xavier Lapillonne
Comments on the observed performance
• The microphysics has the largest compute intensity (with respect to memory access) and as such is more suited for the GPU.
• The lower speed up observed for the radiation is quite relative, and essentially comes from the fact that it is very well optimized and is vectorized on the CPU (~9% Peak performance)
• The turbulence scheme requires more memory access.
Next steps
• Port turbtran subroutine with pgi + additional test and optimizations (october 2011)
• Further investigation of radiation and turbulence schemes with Cray directives (november 2011)
• GPU version of microphysics + radiation + turbulence inside COSMO (november-december 2011)
13 06/09/2011, COSMO GM Xavier Lapillonne
Outline
• Physics with 2d data structure
• Porting the physical parametrization to GPU using directives
• Running COSMO on an hybrid GPU-CPU system
14 06/09/2011, COSMO GM Xavier Lapillonne
Possible future implementations in COSMO
Dynamic Microphysics Turbulence Radiation
Phys. parametrization
I/O
GPU
Dynamic Microphysics Turbulence Radiation
Phys. parametrization
I/O
GPU GPU GPU GPU
• Data movement for each routine
• “Full GPU” : Data remain on device, only send to CPU for I/O and communication
C++ - CUDA Directives
15 06/09/2011, COSMO GM Xavier Lapillonne
Running COSMO-2 on Hybrid-system
Multicores Processor
GPUs
• One (or more) multicores CPU
• Domain decomposition
• One GPU per subdomain.
16 06/09/2011, COSMO GM Xavier Lapillonne
Summary
• Porting of the microphysics, radiation and turbulence scheme on GPU was successfully carried out using a directive based approach
• Comparing with a 12 cores CPU, a speed up between 2.4x and 6.5x was observed using one Fermi GPU card
• These results are within the expected values considering hardware properties
• The large overhead of data transfer shows that the “full GPU” approach (i.e. data remains on the GPU, all computation on the device) is the prefered approach for COSMO
17 06/09/2011, COSMO GM Xavier Lapillonne
Additional slides
18 06/09/2011, COSMO GM Xavier Lapillonne
Comparison between PGI and OMP-acc
!$acc data region local(a)!time loopdo itime=1,nt !initialization !$acc region do k=1,nlev do i=1,N a(i,k)=0.0D0 end do end do !$acc end region
! first layer !$acc region do kernel do i=1,N a(i,1)=0.1D0 end do !$acc end region
! vertical computation !$acc region do kernel do i=1,N do k=2,nlev a(i,k)=0.95D0*a(i,k-1)+exp(-2*a(i,k)**2)*a(i,k) end do end do !$acc end region end do ! end time loop!$acc update host(a)!$acc end data region
!$omp acc_data acc_shared(a) !time loopdo itime=1,nt !initialization !$omp acc_region_loop do k=1,nlev do i=1,N a(i,k)=0.0D0 end do end do !$omp end acc_region loop
! first layer !$omp acc_region_loop do i=1,N a(i,1)=0.1D0 end do !$omp end acc_region_loop
! vertical computation !$omp acc_region_loop kernel do i=1,N do k=2,nlev a(i,k)=0.95D0*a(i,k-1)+exp(-2*a(i,k)**2)*a(i,k) end do end do !$omp end acc_region_loop end do ! end time loop!$omp acc_update host(a)!$omp end acc_data
19 06/09/2011, COSMO GM Xavier Lapillonne
MAIN_ / mo_gscp_dwd_hydci_pp_ _ (x10)------------------------------------------------------------------------User time (approx) 2.999 secs 7197500711 cyclesSystem to D1 refill 2.434M/sec 7300271 linesSystem to D1 bandwidth 148.576MB/sec 467217344 bytesD2 to D1 bandwidth 1025.770MB/sec 3225672832 bytesL2 to System BW per core 140.940MB/sec 443203504 bytes
HW FP Ops / User time 435.162M/sec 1308546592 ops 4.5%peak(DP)
MAIN_ / src_radiation_fesft_ (x1)------------------------------------------------------------------------ User time (approx) 7.226 secs 17342858074 cycles 100.0%Time System to D1 refill 11.380M/sec 82232710 lines System to D1 bandwidth 694.569MB/sec 5262893440 bytes D2 to D1 bandwidth 1162.252MB/sec 8806624128 bytes L2 to System BW per core 645.679MB/sec 4892446080 bytes HW FP Ops / User time 893.252M/sec 6511701846 ops 9.3%peak(DP)
Craypat infos
MAIN_ / turbulence_diff_ref_turbdiff_ (x10)------------------------------------------------------------------------ User time (approx) 4.397 secs 10551890928 cycles 100.0%Time System to D1 refill 15.757M/sec 69278266 lines System to D1 bandwidth 961.741MB/sec 4433809024 bytes D2 to D1 bandwidth 485.462MB/sec 2238073856 bytes L2 to System BW per core 982.474MB/sec 4529394160 bytes HW FP Ops / User time 326.405M/sec 1452061875 ops 3.4%peak(DP)
20 06/09/2011, COSMO GM Xavier Lapillonne
Palu Results
21 06/09/2011, COSMO GM Xavier Lapillonne
Results, microphysics, double precision, Palu
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
1 CPU (12 cores)
2 CPU (24 cores)
GPU-Fermi C
ray
GPU-Fermi P
GI
Sp
eed
up
(D
P)
speedup without datatransfer
speedup including datatransfer
22 06/09/2011, COSMO GM Xavier Lapillonne
Results, Radiation, double precision, Palu
0.00
0.50
1.00
1.50
2.00
2.50
3.00
1 CPU (12 co
res)
2 CPU (24 co
res)
GPU-Fermi C
ray
GPU-Fermi P
GI
Sp
ee
d u
p (
DP
)
speedup without datatransfer
speedup including datatransfer
23 06/09/2011, COSMO GM Xavier Lapillonne
Results, Turbulence, double precision, Palu
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
1 CPU (12 cores)
2 CPU (24 cores)
GPU-Fermi C
ray
GPU-Fermi P
GI
Sp
ee
d u
p (
DP
)
speedup without datatransfer
speedup includingdata transfer
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