# LUMI-G training
We assume that you have already allocated resources with `salloc`
`cp -r /projappl/project_465000320/exercises/AMD/HIP-Examples/ .`
## Basic examples
`cd HIP-Examples/vectorAdd`
Examine files here – README, Makefile and vectoradd_hip.cpp Notice that Makefile requires HIP_PATH to be set. Check with module show rocm or echo $HIP_PATH Also, the Makefile builds and runs the code. We’ll do the steps separately. Check also the HIPFLAGS in the Makefile.
```
make vectoradd_hip.exe
srun -n 1 ./vectoradd_hip.exe
```
Now let’s try the cuda-stream example. This example is from the original McCalpin code as ported to CUDA by Nvidia. This version has been ported to use HIP. See add4 for another similar stream example.
```
cd HIP-Examples/cuda-stream
make
srun -n 1 ./stream
```
Note that it builds with the hipcc compiler. You should get a report of the Copy, Scale, Add, and Triad cases.
Check that we need to declare target GPU for MI250x, is the `--offload-arch=gfx90a`
## Hipify example
We’ll use the same HIP-Examples that were downloaded for the first exercise Get a node allocation.
### Exercise 1: Manual code conversion from CUDA to HIP (10 min)
Choose one or more of the CUDA samples in HIP-Examples/mini-nbody/cuda repository and manually convert them to HIP.
Some code suggestions include mini-nbody/cuda/<nbody-block.cu,nbody-orig.cu,nbody-soa.cu>
The CUDA samples are located in HIP-Examples/mini-nbody/cuda
Manually convert the source code of your choice to HIP
You’ll want to compile on the node you’ve been allocated so that hipcc will choose the correct GPU architecture.
### Exercise 2: Code conversion from CUDA to HIP using HIPify tools (10 min)
Use the `hipify-perl.sh -inplace -print-stats` to “hipify” the CUDA samples you used to manually convert to HIP in Exercise 1. hipify-perl.sh is in `$ROCM_PATH/hip/bin` directory and should be in your path.
* For example, if helloworld.cu is a CUDA program, run hipify-perl.sh -inplace –print-stats helloworld.cu. You’ll see a helloworld.cu.prehip file that is the original and the helloworld.cu file now has HIP calls. b. You’ll also see statistics of HIP APIs that were converted. For example, for hipify-perl.sh -inplace -print-stats nbody-orig.cu:
```
[HIPIFY] info: file 'nbody-orig.cu' statistics:
CONVERTED refs count: 7
TOTAL lines of code: 91
WARNINGS: 0
[HIPIFY] info: CONVERTED refs by names:
cudaFree => hipFree: 1
cudaMalloc => hipMalloc: 1
cudaMemcpyDeviceToHost => hipMemcpyDeviceToHost: 1
cudaMemcpyHostToDevice => hipMemcpyHostToDevice: 1
```
* Compile the HIP programs. Fix any compiler issues, for example, if there was something that didn’t hipify correctly. Be on the lookout for hard-coded Nvidia specific things like warp sizes and PTX. For the nbody-orig.cu code, compile with hipcc -DSHMOO -I ../ nbody-orig.cu -o nbody-orig. The #define SHMOO fixes some timer printouts. Add --offload-arch=<gpu_type> to specify the GPU type and avoid the autodetection issues when running on a single GPU on a node.
* Run the programs.
## Profiling Tools
### Rocprof
* Get the exercise:
https://github.com/ROCm-Developer-Tools/HIP-Examples/tree/master/mini-nbody
* Compile and run the code
```
cd mini-nbody/hip
```
Can compile and run all with
```
./HIP-nbody-orig.sh
```
Or just run compile and run one case
```
hipcc -I../ -DSHMOO nbody-orig.cpp -o nbody-orig
./nbody-orig 65536
65536, 161.871
```
* Note that we can find the compile line and the executable name by checking the file `HIP-nbody-orig.sh` or by watching the output from running the script.
```
cat HIP-nbody-orig.sh
...
EXE=nbody-orig
...
./$EXE 65536
...
```
* The binary is called `nbody-orig`
* Use rocprof with `--stats`
```
rocprof --stats nbody-orig 65536
RPL: on '221130_200946' from '/global/software/rocm/rocm-5.3.0' in '/global/home/gmarko/HIP-Examples/mini-nbody/hip'
RPL: profiling '"nbody-orig" "65536"'
RPL: input file ''
RPL: output dir '/tmp/rpl_data_221130_200946_3670592'
RPL: result dir '/tmp/rpl_data_221130_200946_3670592/input_results_221130_200946'
ROCProfiler: input from "/tmp/rpl_data_221130_200946_3670592/input.xml"
0 metrics
65536, 159.960
ROCPRofiler: 10 contexts collected, output directory /tmp/rpl_data_221130_200946_3670592/input_results_221130_200946
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.csv' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.stats.csv' is generating
```
Files with the prefix results are created
* Check the files results.csv
You can see information for each kernel call with their duration
```
cat results.csv
"Index","KernelName","gpu-id","queue-id","queue-index","pid","tid","grd","wgr","lds","scr","arch_vgpr","accum_vgpr","sgpr","wave_size","sig","obj","DispatchNs","BeginNs","EndNs","CompleteNs","DurationNs"
0,"bodyForce(Body*, float, int) [clone .kd]",0,0,0,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372809346673,1591372809872935,1591372836189584,1591372836215944,26316649
1,"bodyForce(Body*, float, int) [clone .kd]",0,0,2,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372836774261,1591372837000949,1591372863116796,1591372863132315,26115847
2,"bodyForce(Body*, float, int) [clone .kd]",0,0,4,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372863652552,1591372863877281,1591372889980009,1591372889994436,26102728
3,"bodyForce(Body*, float, int) [clone .kd]",0,0,6,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372890512133,1591372890735562,1591372916796147,1591372916817087,26060585
4,"bodyForce(Body*, float, int) [clone .kd]",0,0,8,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372917332974,1591372917556629,1591372943652575,1591372943667909,26095946
5,"bodyForce(Body*, float, int) [clone .kd]",0,0,10,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372944181896,1591372944405378,1591372970475883,1591372970491020,26070505
6,"bodyForce(Body*, float, int) [clone .kd]",0,0,12,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372971009527,1591372971233309,1591372997318181,1591372997339821,26084872
7,"bodyForce(Body*, float, int) [clone .kd]",0,0,14,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591372997856209,1591372998080743,1591373024164495,1591373024180993,26083752
8,"bodyForce(Body*, float, int) [clone .kd]",0,0,16,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591373024701060,1591373024924818,1591373051023611,1591373051040364,26098793
9,"bodyForce(Body*, float, int) [clone .kd]",0,0,18,3670615,3670615,65536,256,0,0,20,4,16,64,"0x0","0x7f7b27c04500",1591373051559851,1591373051782878,1591373077878145,1591373077902255,26095267
```
* Check the statistics result file, one line per kernel
```
cat results.stats.csv
"Name","Calls","TotalDurationNs","AverageNs","Percentage"
"bodyForce(Body*, float, int) [clone .kd]",10,261124944,26112494,100.0
```
* Profile the HIP calls with `--hip-trace`
```
rocprof --stats --hip-trace nbody-orig 65536
RPL: on '221130_201416' from '/global/software/rocm/rocm-5.3.0' in '/global/home/gmarko/HIP-Examples/mini-nbody/hip'
RPL: profiling '"nbody-orig" "65536"'
RPL: input file ''
RPL: output dir '/tmp/rpl_data_221130_201416_3670892'
RPL: result dir '/tmp/rpl_data_221130_201416_3670892/input_results_221130_201416'
ROCTracer (pid=3670915):
HIP-trace()
65536, 161.051
hsa_copy_deps: 0
scan ops data 29:30 File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.copy_stats.csv' is generating
dump json 19:20
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.hip_stats.csv' is generating
dump json 51:52
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.stats.csv' is generating
dump json 9:10
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
```
Now we have new files with the `hip` in their name like below, check the file `results.hip_stats.csv`
```
cat results.hip_stats.csv
"Name","Calls","TotalDurationNs","AverageNs","Percentage"
"hipMemcpy",20,486845521,24342276,99.89375113830629
"hipLaunchKernel",10,467008,46700,0.09582337501179998
"hipMalloc",1,30570,30570,0.006272527610042495
"hipFree",1,14210,14210,0.0029156891507590398
"__hipPushCallConfiguration",10,3510,351,0.0007202018943817191
"__hipPopCallConfiguration",10,2520,252,0.0005170680267355932
```
* Profile also the HSA API with the `--hsa-trace`
```
rocprof --stats --hip-trace --hsa-trace nbody-orig 65536
RPL: on '221130_201737' from '/global/software/rocm/rocm-5.3.0' in '/global/home/gmarko/HIP-Examples/mini-nbody/hip'
RPL: profiling '"nbody-orig" "65536"'
RPL: input file ''
RPL: output dir '/tmp/rpl_data_221130_201737_3671219'
RPL: result dir '/tmp/rpl_data_221130_201737_3671219/input_results_221130_201737'
ROCProfiler: input from "/tmp/rpl_data_221130_201737_3671219/input.xml"
0 metrics
ROCTracer (pid=3671242):
HSA-trace()
HSA-activity-trace()
HIP-trace()
65536, 155.978
ROCPRofiler: 10 contexts collected, output directory /tmp/rpl_data_221130_201737_3671219/input_results_221130_201737
hsa_copy_deps: 1
scan hsa API data 5953:5954 hsa_copy_deps: 0
scan hip API data 51:52 File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.csv' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.stats.csv' is generating
dump json 9:10
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.hsa_stats.csv' is generating
dump json 5963:5964
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.copy_stats.csv' is generating
dump json 19:20
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.hip_stats.csv' is generating
dump json 51:52
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/results.json' is generating
```
* See the content of the file `results.hsa_stats.csv`
```
cat results.hsa_stats.csv
"Name","Calls","TotalDurationNs","AverageNs","Percentage"
"hsa_signal_wait_scacquire",50,264955082,5299101,82.69977799679005
"hsa_queue_create",1,39868279,39868279,12.443987854568068
"hsa_amd_memory_async_copy",20,4917141,245857,1.5347751249357586
"hsa_amd_signal_async_handler",20,4262555,213127,1.3304608069344652
"hsa_signal_store_screlease",40,1945998,48649,0.60739956889069
"hsa_amd_memory_lock_to_pool",20,1418202,70910,0.44265990170591873
"hsa_amd_memory_unlock",20,723957,36197,0.22596691758953363
"hsa_agent_get_info",80,671007,8387,0.20943976433821374
"hsa_amd_memory_pool_allocate",5,597926,119585,0.18662917157599068
"hsa_system_get_info",5005,367139,73,0.11459419296574767
"hsa_executable_load_agent_code_object",2,216629,108314,0.0676158768966984
"hsa_executable_freeze",2,156380,78190,0.048810504729771616
"hsa_amd_agents_allow_access",4,89470,22367,0.02792605101785821
"hsa_signal_create",57,51500,903,0.016074568318092074
"hsa_code_object_reader_create_from_memory",2,20940,10470,0.006535950690890253
"hsa_isa_get_info_alt",2,18180,9090,0.005674478680056581
"hsa_signal_load_relaxed",236,17880,75,0.005580840418009442
"hsa_system_get_major_extension_table",3,14920,4973,0.004656942899144344
"hsa_amd_profiling_get_async_copy_time",40,13430,335,0.004191872864310224
"hsa_executable_create_alt",2,9030,4515,0.0028185116876188626
"hsa_amd_memory_pool_get_info",106,7570,71,0.002362805478989456
"hsa_amd_agent_iterate_memory_pools",27,7440,275,0.0023222288987690297
"hsa_amd_memory_pool_free",1,4710,4710,0.0014701207141400712
"hsa_executable_get_symbol_by_name",15,3599,239,0.0011233470170255023
"hsa_queue_add_write_index_screlease",20,3500,175,0.0010924463905499467
"hsa_amd_profiling_get_dispatch_time",20,3110,155,0.0009707166498886669
"hsa_signal_silent_store_relaxed",40,2800,70,0.0008739571124399574
"hsa_amd_agent_memory_pool_get_info",19,2490,131,0.0007771975749912477
"hsa_iterate_agents",2,2250,1125,0.0007022869653535371
"hsa_queue_load_read_index_relaxed",20,2240,112,0.0006991656899519659
"hsa_signal_destroy",20,2190,109,0.0006835593129441095
"hsa_queue_load_read_index_scacquire",20,1790,89,0.0005587082968812585
"hsa_executable_symbol_get_info",30,1540,51,0.00048067641184197657
"hsa_amd_profiling_async_copy_enable",1,440,440,0.00013733611766913615
"hsa_agent_iterate_isas",1,400,400,0.00012485101606285104
"hsa_amd_profiling_set_profiler_enabled",1,140,140,4.3697855621997866e-05
"hsa_dispatch",10,0,0,0.0
```
* Download the results.json file on your laptop
From your laptop:
`scp username@lumi.csc.fi:/path/results.json .`
* Visit the web page:
https://ui.perfetto.dev/
* Click on the top left menu, "Open Trace File on th eleft top"
* Select the file results.json
Zoom in/out: W/S
Move left/right: A/D
Read about the counters: ` vim /opt/rocm/rocprofiler/lib/gfx_metrics.xml`
* Create a file with the contents:
```
cat rocprof_counters.txt
pmc : Wavefronts VALUInsts VFetchInsts VWriteInsts VALUUtilization VALUBusy WriteSize
pmc : SALUInsts SFetchInsts LDSInsts FlatLDSInsts GDSInsts SALUBusy FetchSize
pmc : L2CacheHit MemUnitBusy MemUnitStalled WriteUnitStalled ALUStalledByLDS LDSBankConflict
```
* Execute with using the counters
```
rocprof --timestamp on -i rocprof_counters.txt nbody-orig 65536
RPL: on '221130_205737' from '/global/software/rocm/rocm-5.3.0' in '/global/home/gmarko/HIP-Examples/mini-nbody/hip'
RPL: profiling '"nbody-orig" "65536"'
RPL: input file 'rocprof_counters.txt'
RPL: output dir '/tmp/rpl_data_221130_205737_3673574'
RPL: result dir '/tmp/rpl_data_221130_205737_3673574/input0_results_221130_205737'
ROCProfiler: input from "/tmp/rpl_data_221130_205737_3673574/input0.xml"
gpu_index =
kernel =
range =
7 metrics
Wavefronts, VALUInsts, VFetchInsts, VWriteInsts, VALUUtilization, VALUBusy, WriteSize
65536, 155.389
ROCPRofiler: 10 contexts collected, output directory /tmp/rpl_data_221130_205737_3673574/input0_results_221130_205737
RPL: result dir '/tmp/rpl_data_221130_205737_3673574/input1_results_221130_205737'
ROCProfiler: input from "/tmp/rpl_data_221130_205737_3673574/input1.xml"
gpu_index =
kernel =
range =
7 metrics
SALUInsts, SFetchInsts, LDSInsts, FlatLDSInsts, GDSInsts, SALUBusy, FetchSize
65536, 156.996
ROCPRofiler: 10 contexts collected, output directory /tmp/rpl_data_221130_205737_3673574/input1_results_221130_205737
RPL: result dir '/tmp/rpl_data_221130_205737_3673574/input2_results_221130_205737'
ROCProfiler: input from "/tmp/rpl_data_221130_205737_3673574/input2.xml"
gpu_index =
kernel =
range =
6 metrics
L2CacheHit, MemUnitBusy, MemUnitStalled, WriteUnitStalled, ALUStalledByLDS, LDSBankConflict
65536, 155.264
ROCPRofiler: 10 contexts collected, output directory /tmp/rpl_data_221130_205737_3673574/input2_results_221130_205737
File '/global/home/gmarko/HIP-Examples/mini-nbody/hip/rocprof_counters.csv' is generating
```
* Contents of the rocprof_counters.csv file
```
cat rocprof_counters.csv
Index,KernelName,gpu-id,queue-id,queue-index,pid,tid,grd,wgr,lds,scr,arch_vgpr,accum_vgpr,sgpr,wave_size,sig,obj,Wavefronts,VALUInsts,VFetchInsts,VWriteInsts,VALUUtilization,VALUBusy,WriteSize,SALUInsts,SFetchInsts,LDSInsts,FlatLDSInsts,GDSInsts,SALUBusy,FetchSize,L2CacheHit,MemUnitBusy,MemUnitStalled,WriteUnitStalled,ALUStalledByLDS,LDSBankConflict,DispatchNs,BeginNs,EndNs,CompleteNs
0,"bodyForce(Body*, float, int) [clone .kd]",0,0,0,3673711,3673711,65536,256,0,0,20,4,16,64,0x0,0x7f2b4d282500,2048.0000000000,1212443.0000000000,12.0000000000,12.0000000000,100.0000000000,68.1476813493,7872.0000000000,131228.5000000000,65553.0000000000,0.0000000000,0.0000000000,0.0000000000,6.3483148000,9429.1875000000,96.5684331443,0.0250344612,0.0044357832,0.0102024550,0.0000000000,0.0000000000,1594244102859719,1594244111978746,1594244138305243,1594244138330792
...
```
### Omnitrace
We have made special builds of the Omnitools, omnitrace and omniperf for use in the exercises
* Reserve a GPU
* Load Omnitrace
Declare `PATH` and `LD_LIBRARY_PATH`
It is temporarily installed here: `/projappl/project_465000320/software/omnitrace/1.7.3`
`export PATH=/projappl/project_465000320/software/omnitrace/1.7.3/bin:$PATH`
`export LD_LIBRARY_PATH=/projappl/project_465000320/software/omnitrace/1.7.3/lib:$LD_LIBRARY_PATH`
* Check the various options and their values and also a second command for description
`srun -n 1 --gpus 1 omnitrace-avail --categories omnitrace`
`srun -n 1 --gpus 1 omnitrace-avail --categories omnitrace --brief --description`
* Create an Omnitrace configuration file with description per option
`srun -n 1 omnitrace-avail -G omnitrace_all.cfg --all`
* Declare to use this configuration file: `export OMNITRACE_CONFIG_FILE=/path/omnitrace_all.cfg`
* Get the file https://github.com/ROCm-Developer-Tools/HIP/tree/develop/samples/2_Cookbook/0_MatrixTranspose/MatrixTranspose.cpp
* Compile ` hipcc -o MatrixTranspose MatrixTranspose.cpp`
* May need to add the GPU architecture
```
hipcc --offload-arch=gfx90a -o MatrixTranspose MatrixTranspose.cpp
```
* Execute the binary: `time srun -n 1 --gpus 1 ./MatrixTranspose` and check the duration
#### Dynamic instrumentation
* Execute dynamic instrumentation: `time srun –n 1 –gpus 1 omnitrace -- ./MatrixTranspose` and check the duration
* Check what the binary calls and gets instrumented: `nm --demangle MatrixTranspose | egrep -i ' (t|u) '`
* Available functions to instrument: `srun -n 1 --gpus 1 omnitrace -v -1 --simulate --print-available functions -- ./MatrixTranspose`
* the simulate option means that it will not execute the binary
#### Binary rewriting
* Binary rewriting: `srun -n 1 --gpus 1 omnitrace -v -1 --print-available functions -o matrix.inst -- ./MatrixTranspose`
* We created a new instrumented binary called matrix.inst
* Executing the new instrumented binary: `time srun -n 1 --gpus 1 ./matrix.inst` and check the duration
* See the list of the instrumented GPU calls: `cat omnitrace-matrix.inst-output/TIMESTAMP/roctracer.txt`
#### Visualization
* Copy the `perfetto-trace.proto` to your laptop, open the web page https://ui.perfetto.dev/ click to open the trace and select the file
#### Hardware counters
* See a list of all the counters: `srun -n 1 --gpus 1 omnitrace-avail --all`
* Declare in your configuration file: `OMNITRACE_ROCM_EVENTS = GPUBusy,Wavefronts,VALUBusy,L2CacheHit,MemUnitBusy`
* Execute: `srun -n 1 --gpus 1 ./matrix.inst` and copy the perfetto file and visualize
#### Sampling
Activate in your configuration file `OMNITRACE_USE_SAMPLING = true` and `OMNITRACE_SAMPLING_FREQ = 100`, execute and visualize
#### Kernel timings
* Open the file `omnitrace-binary-output/timestamp/wall_clock.txt` (replace binary and timestamp with your information)
* In order to see the kernels gathered in your configuration file, make sure that `OMNITRACE_USE_TIMEMORY = true` and `OMNITRACE_FLAT_PROFILE = true`, execute the code and open again the file `omnitrace-binary-output/timestamp/wall_clock.txt`
### Omniperf
We have made special builds of the Omnitools, omnitrace and omniperf for use in the exercises
* Load Omniperf:
`export PATH=/projappl/project_465000320/software/omniperf/1.0.6/bin/:$PATH`
`export PYTHONPATH=/projappl/project_465000320/software/omniperf/puthon-libs:$PYTHONPATH`
`module load cray-python`
`module load rocm`
* Reserve a GPU, compile the exercise and execute Omniperf, observe how many times the code is executed
```
`salloc -p gpu --gpus 1 -t 00:40:00`
cp /path/omniperf/1.0.4/share/sample/vcopy.cpp .
hipcc -o vcopy vcopy.cpp
srun -n 1 --gpus 1 omniperf profile -n vcopy_all -- ./vcopy 1048576 256
```
* Run `srun -n 1 --gpus 1 omniperf profile -h` to see all the options
* Now is created a workload in the directory workloads with the name vcopy_all (the argument of the -n). So, we can analyze it
```
srun -n 1 --gpus 1 omniperf analyze -p workloads/vcopy_all/mi200/ &> vcopy_analyze.txt
```
* If you want to only roofline analysis, then execute: `srun -n 1 --gpus 1 omniperf profile -n vcopy_all --roof-only -- ./vcopy 1048576 256`
There is no need for srun to analyze but we want to avoid everybody to use the login node. Explore the file `vcopy_analyze.txt`
* We can select specific IP Blocks, like:
```
srun -n 1 --gpus 1 omniperf analyze -p workloads/vcopy_all/mi200/ -b 7.1.2
```
But you need to know the code of the IP Block
* If you have installed Omniperf on your laptop (no ROCm required for analysis) then you can download the data and execute:
```
omniperf analyze -p workloads/vcopy_all/mi200/ --gui
```
* Open the web page: http://IP:8050/ The IP will be displayed in the output
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