Compile and deploy QNN models to S24 (#5137)

Summary: Pull Request resolved: #5137

Reviewed By: huydhn

Differential Revision: D62328317

Pulled By: guangy10

fbshipit-source-id: c38d9dc9562d273a3add8972abcf427aec31c68f

Author: Guang Yang

.ci/scripts/test_model.sh

@@ -177,6 +177,7 @@ test_model_with_qnn() {
   fi
 
   # Use SM8450 for S22, SM8550 for S23, and SM8560 for S24
+  # TODO(guangyang): Make QNN chipset matches the target device
   QNN_CHIPSET=SM8450
 
   "${PYTHON_EXECUTABLE}" -m examples.qualcomm.scripts.${EXPORT_SCRIPT} -b ${CMAKE_OUTPUT_DIR} -m ${QNN_CHIPSET} --compile_only

.github/workflows/android-perf.yml

@@ -105,6 +105,7 @@ jobs:
           # Mapping devices to their corresponding device-pool-arn
           declare -A DEVICE_POOL_ARNS
           DEVICE_POOL_ARNS[samsung_galaxy_s22]="arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/e59f866a-30aa-4aa1-87b7-4510e5820dfa"
+          DEVICE_POOL_ARNS[samsung_galaxy_s24]="arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/98f8788c-2e25-4a3c-8bb2-0d1e8897c0db"
 
           # Resolve device names with their corresponding ARNs
           if [[ ! $(echo "$DEVICES" | jq empty 2>/dev/null) ]]; then