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@lamikr lamikr commented Jan 31, 2025

RX 7800 XT results from Bazza-63

lamikr and others added 28 commits June 7, 2024 12:39
- AMD GPU benchmarks works on rocm platform
  (tested on rocm 6.1.1) and offers support
  of using CUDA api with AMD gpus
- only code change is needed is to test.sh
  to check whether rocm-smi tool is available
  and whether it returns AMD GPUs
- rocm-smi can be used to query the AMD gpu count
- I had pytorch 2.3.0 and pytorch vision 0.18.0 installed
  with AMD rocm support enabled and all tests executed
  without errors on AMD RX 6800

Signed-off-by: Mika Laitio <[email protected]>
(cherry picked from commit 1d0d0aa)
- rename and rearragne resutls to be more consistently named
  and organized
- separate multi-gpu results from single gpu results
- use underscrore instead of space on names
- each folder will only contain one set of benchmark results
- separate amd and nvidia results to own subfolders

Signed-off-by: Mika Laitio <[email protected]>
- allow specifying gpu-index parameter in addition
  of gpu-count parameter.
- gpu index parameter can be used to request the benchmarks
  to be run only of certain gpu index in multi-gpu case
- if more than one gpu, run benchmarks separately for each
  and then in the end run tests with all gpus used at a same time
- fixes for: lamikr/rocm_sdk_builder#63

Signed-off-by: Mika Laitio <[email protected]>
use pytorch script to get device count instead
of using amd or nvidia gpu specific commands and
then execute the benchmark for each gpu found.

Signed-off-by: Mika Laitio <[email protected]>
Signed-off-by: Mika Laitio <[email protected]>
- defined minimal, medium and full set of models
- use the amount of gpu memory as a criteria
  whether to run minimal. medium or full set of models
  (8GB device can run medium set without getting
   out of memory error)

Signed-off-by: Mika Laitio <[email protected]>
- datafiles to be plotted must still be
  hardcoded in the code as a list
- can show graphs that can be used to compare
  results from multiple amd and nvidia gpus
- problem when showing the results is that
  the benchmarks that have been run on different
  GPU's have varied during the time. The list of
  benchmarks in full set is nowadays much bigger
  than on rx 1080/2060 release time.

Signed-off-by: Mika Laitio <[email protected]>
- select more in detail which type of benchmarks
  are run depending from the amount of memery available
  (benchmarks executed for dounle type can be different than
   float type for example)

Signed-off-by: Mika Laitio <[email protected]>
- add first benchmark results with the
  framework 16 laptop which has both the
  discrete 7700S gpu and internal M780M iGPU.
- tests were executed with rocm sdk builder v6.1.2 version

Signed-off-by: Mika Laitio <[email protected]>
Signed-off-by: Mika Laitio <[email protected]>
Signed-off-by: Mika Laitio <[email protected]>
- fixes the problem where the column
  resnet101 was by default before the resnet34 column

Signed-off-by: Mika Laitio <[email protected]>
- latest rocm sdk builder has pytorch optimization in aotriton
  provided flash attenation algorithm for gfx1100/gfx1101/gfx1102
  and gfx1103.

Signed-off-by: Mika Laitio <[email protected]>
Signed-off-by: Mika Laitio <[email protected]>
- improvements to logic that is used
  for selecting which models and precicious
  are benchmarked based on the amount of
  memory available on gpu

Signed-off-by: Mika Laitio <[email protected]>
Signed-off-by: Mika Laitio <[email protected]>
- trainign --> train
- single --> float

for couple of nvidia benchmarks which used different
naming than other results

Signed-off-by: Mika Laitio <[email protected]>
- execute at least 2 models also on small
  model case to allow showing line graphs
  easier

Signed-off-by: Mika Laitio <[email protected]>
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2 participants