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[NPU][CI] Add CANN 9.1.0 and Ascend a5 nightly suites (#38833)

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This commit is contained in:
pllimax
2026-09-14 22:39:42 +08:00
committed by GitHub
parent 433c999dd0
commit 7465e42b7a
8 changed files with 323 additions and 135 deletions
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.github/workflows/_npu-single-node-test-stage.yml
+1
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@@ -345,6 +345,7 @@ jobs:
source /usr/local/Ascend/nnal/atb/set_env.sh || true
source /usr/local/Ascend/ascend-toolkit/latest/opp/vendors/customize/bin/set_env.bash || true
source /usr/local/Ascend/ascend-toolkit/latest/opp/vendors/custom_transformer/bin/set_env.bash || true
source /usr/local/Ascend/ascend-toolkit/latest/set_env.sh || true
set -u
# Nightly log path mirrors the output layout; PR keeps the original {date}/{testcase}.
.github/workflows/nightly-test-npu.yml
+166 -3
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@@ -29,6 +29,16 @@ on:
required: false
type: string
default: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/dockerhub/lmsysorg/sglang:main-cann9.0.0-a3'
image_a3_cann910:
description: 'The a3 running docker image of the test task with cann 9.1.0.'
required: false
type: string
default: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/dockerhub/lmsysorg/sglang:cann9.1.0-a3-nightly'
image_a5:
description: 'The a5 running docker image of the test task.'
required: false
type: string
default: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/dockerhub/lmsysorg/sglang:cann9.1.0-950-nightly'
skip_install_flag:
description: 'Indicates whether to skip the installation of sglang, defaulting to false.'
required: false
@@ -56,6 +66,16 @@ on:
required: false
type: string
default: ''
image_a3_cann910:
description: 'The a3 running docker image of the test task with cann 9.1.0.'
required: false
type: string
default: ''
image_a5:
description: 'The a5 running docker image of the test task.'
required: false
type: string
default: ''
skip_install_flag:
description: 'Indicates whether to skip the installation of sglang, defaulting to false.'
required: false
@@ -72,6 +92,8 @@ jobs:
job_filter: ${{ steps.set-vars.outputs.job_filter }}
image_a2: ${{ steps.set-vars.outputs.image_a2 }}
image_a3: ${{ steps.set-vars.outputs.image_a3 }}
image_a3_cann910: ${{ steps.set-vars.outputs.image_a3_cann910 }}
image_a5: ${{ steps.set-vars.outputs.image_a5 }}
skip_install_flag: ${{ steps.set-vars.outputs.skip_install_flag }}
run_start_metadata: ${{ steps.set-vars.outputs.run_start_metadata }}
steps:
@@ -103,6 +125,16 @@ jobs:
else
echo "image_a3=${{ inputs.image_a3 }}" >> $GITHUB_OUTPUT
fi
if [ -z "${{ inputs.image_a3_cann910 }}" ]; then
echo "image_a3_cann910=swr.cn-southwest-2.myhuaweicloud.com/base_image/dockerhub/lmsysorg/sglang:cann9.1.0-a3-nightly" >> $GITHUB_OUTPUT
else
echo "image_a3_cann910=${{ inputs.image_a3_cann910 }}" >> $GITHUB_OUTPUT
fi
if [ -z "${{ inputs.image_a5 }}" ]; then
echo "image_a5=swr.cn-southwest-2.myhuaweicloud.com/base_image/dockerhub/lmsysorg/sglang:cann9.1.0-950-nightly" >> $GITHUB_OUTPUT
else
echo "image_a5=${{ inputs.image_a5 }}" >> $GITHUB_OUTPUT
fi
if [ -z "${{ inputs.skip_install_flag }}" ]; then
echo "skip_install_flag=false" >> $GITHUB_OUTPUT
else
@@ -282,6 +314,56 @@ jobs:
device_type_for_deps: 'a3'
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
nightly-acc-4-npu-a5:
name: nightly-acc-4-npu-a5
if: ${{ !cancelled() }}
needs: [set-image-config]
uses: ./.github/workflows/_npu-single-node-test-stage.yml
with:
runner: linux-amd64-a5-4
test_type: 'accuracy'
test_suite: nightly-acc-4-npu-a5
is_nightly_pipeline_job: true
skip_pr_test_health_check: 'true'
image: ${{ needs.set-image-config.outputs.image_a5 }}
install_sglang_deps: false
device_type_for_deps: 'a5'
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
# Suites suffixed with `-cann910` run against the CANN 9.1.0 image.
nightly-perf-16-npu-a3-cann910:
name: nightly-perf-16-npu-a3-cann910
if: ${{ !cancelled() }}
needs: [set-image-config]
uses: ./.github/workflows/_npu-single-node-test-stage.yml
with:
runner: linux-aarch64-a3-800t-16
test_type: 'perf'
test_suite: nightly-perf-16-npu-a3-cann910
is_nightly_pipeline_job: true
skip_pr_test_health_check: 'true'
image: ${{ needs.set-image-config.outputs.image_a3_cann910 }}
install_sglang_deps: false
device_type_for_deps: 'a3'
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
test_timeout_minutes: '180'
nightly-acc-16-npu-a3-cann910:
name: nightly-acc-16-npu-a3-cann910
if: ${{ !cancelled() }}
needs: [set-image-config]
uses: ./.github/workflows/_npu-single-node-test-stage.yml
with:
runner: linux-aarch64-a3-16-
test_type: 'accuracy'
test_suite: nightly-acc-16-npu-a3-cann910
is_nightly_pipeline_job: true
skip_pr_test_health_check: 'true'
image: ${{ needs.set-image-config.outputs.image_a3_cann910 }}
install_sglang_deps: false
device_type_for_deps: 'a3'
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
nightly-poc-multi-node-tests:
name: multi-node-poc
if: ${{ !cancelled() }}
@@ -362,6 +444,72 @@ jobs:
transformers_version: ''
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
nightly-poc-multi-node-tests-cann910:
name: multi-node-poc-cann910
if: ${{ !cancelled() }}
# Multi-node jobs run strictly one at a time to avoid contending for the
# same A3 multi-node resources: 9.0.0 multi -> 9.0.0 mix -> cann910 multi -> cann910 mix.
needs: [set-image-config, nightly-perf-16-npu-a3-cann910, nightly-acc-16-npu-a3-cann910, nightly-poc-multi-node-tests, nightly-poc-multi-node-mix-tests]
strategy:
fail-fast: false
max-parallel: 1
matrix:
test_config:
# deepseek_v4_flash performance tests
- name: deepseek_v4_flash_w8a8_1p1d_16p_in8k_out1k_50ms
prefill_size: 1
decode_size: 1
router_size: 1
test_case: test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_1p1d_16p_in8k_out1k_50ms.py
test_type: 'perf'
prefill_decode_deployment: 'separation'
uses: ./.github/workflows/nightly-test-npu-e2e-multi-node.yml
with:
runner: linux-amd64-cpu-4
test_type: ${{ matrix.test_config.test_type || 'perf' }}
test_config_name: ${{ matrix.test_config.name }}
prefill_size: ${{ matrix.test_config.prefill_size }}
decode_size: ${{ matrix.test_config.decode_size }}
router_size: ${{ matrix.test_config.router_size }}
test_case: ${{ matrix.test_config.test_case }}
image: ${{ needs.set-image-config.outputs.image_a3_cann910 }}
install_sglang_from_source: false
prefill_decode_deployment: ${{ matrix.test_config.prefill_decode_deployment }}
transformers_version: ''
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
nightly-poc-multi-node-mix-tests-cann910:
name: multi-node-mix-poc-cann910
if: ${{ !cancelled() }}
needs: [set-image-config, nightly-poc-multi-node-tests-cann910]
strategy:
fail-fast: false
max-parallel: 1
matrix:
test_config:
# glm_5_2 accuracy tests
- name: glm_5_2_w4a8_16p_gpqa
node_size: 2
test_case: test/registered/npu/accuracy/glm5_2/test_npu_glm_5_2_w4a8_16p_gpqa.py
test_type: 'accuracy'
# kimi_k3 accuracy tests
- name: kimi_k3_w4a8_32p_gpqa
node_size: 4
test_case: test/registered/npu/accuracy/kimi_k3/test_npu_kimi_k3_w4a8_32p_gpqa.py
test_type: 'accuracy'
uses: ./.github/workflows/nightly-test-npu-e2e-multi-node.yml
with:
runner: linux-amd64-cpu-4
test_type: ${{ matrix.test_config.test_type || 'perf' }}
test_config_name: ${{ matrix.test_config.name }}
node_size: ${{ matrix.test_config.node_size }}
test_case: ${{ matrix.test_config.test_case }}
image: ${{ needs.set-image-config.outputs.image_a3_cann910 }}
install_sglang_from_source: false
prefill_decode_deployment: 'mix'
transformers_version: ''
run_start_metadata: ${{ needs.set-image-config.outputs.run_start_metadata }}
check-all-jobs:
if: ${{ !cancelled() }}
needs:
@@ -375,14 +523,21 @@ jobs:
- nightly-perf-16-npu-a3
- nightly-acc-2-npu-a3
- nightly-acc-16-npu-a3
- nightly-perf-16-npu-a3-cann910
- nightly-acc-16-npu-a3-cann910
- nightly-acc-4-npu-a5
- nightly-poc-multi-node-tests
- nightly-poc-multi-node-mix-tests
- nightly-poc-multi-node-tests-cann910
- nightly-poc-multi-node-mix-tests-cann910
runs-on: ubuntu-latest
steps:
- name: Generate results table
run: |
multi_result="${{ needs.nightly-poc-multi-node-tests.result }}"
mix_result="${{ needs.nightly-poc-multi-node-mix-tests.result }}"
multi_cann910_result="${{ needs.nightly-poc-multi-node-tests-cann910.result }}"
mix_cann910_result="${{ needs.nightly-poc-multi-node-mix-tests-cann910.result }}"
# single-node suites are reported per suite; overall status is success if none failed
single_result="success"
@@ -396,7 +551,10 @@ jobs:
"${{ needs.nightly-perf-4-npu-a3.result }}" \
"${{ needs.nightly-perf-16-npu-a3.result }}" \
"${{ needs.nightly-acc-2-npu-a3.result }}" \
"${{ needs.nightly-acc-16-npu-a3.result }}"; do
"${{ needs.nightly-acc-16-npu-a3.result }}" \
"${{ needs.nightly-perf-16-npu-a3-cann910.result }}" \
"${{ needs.nightly-acc-16-npu-a3-cann910.result }}" \
"${{ needs.nightly-acc-4-npu-a5.result }}"; do
if [ "${r}" != "success" ] && [ "${r}" != "skipped" ]; then
single_result="failure"
fi
@@ -426,17 +584,22 @@ jobs:
"nightly-perf-4-npu-a3:${{ needs.nightly-perf-4-npu-a3.result }}" \
"nightly-perf-16-npu-a3:${{ needs.nightly-perf-16-npu-a3.result }}" \
"nightly-acc-2-npu-a3:${{ needs.nightly-acc-2-npu-a3.result }}" \
"nightly-acc-16-npu-a3:${{ needs.nightly-acc-16-npu-a3.result }}"; do
"nightly-acc-16-npu-a3:${{ needs.nightly-acc-16-npu-a3.result }}" \
"nightly-perf-16-npu-a3-cann910:${{ needs.nightly-perf-16-npu-a3-cann910.result }}" \
"nightly-acc-16-npu-a3-cann910:${{ needs.nightly-acc-16-npu-a3-cann910.result }}" \
"nightly-acc-4-npu-a5:${{ needs.nightly-acc-4-npu-a5.result }}"; do
suite="${entry%%:*}"
r="${entry##*:}"
echo "| ${suite} | $(group_icon ${r}) ${r} |" >> $GITHUB_STEP_SUMMARY
done
echo "| multi-node-poc | $(group_icon ${multi_result}) ${multi_result} |" >> $GITHUB_STEP_SUMMARY
echo "| multi-node-mix-poc | $(group_icon ${mix_result}) ${mix_result} |" >> $GITHUB_STEP_SUMMARY
echo "| multi-node-poc-cann910 | $(group_icon ${multi_cann910_result}) ${multi_cann910_result} |" >> $GITHUB_STEP_SUMMARY
echo "| multi-node-mix-poc-cann910 | $(group_icon ${mix_cann910_result}) ${mix_cann910_result} |" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
FAIL=0
for r in "${single_result}" "${multi_result}" "${mix_result}"; do
for r in "${single_result}" "${multi_result}" "${mix_result}" "${multi_cann910_result}" "${mix_cann910_result}"; do
if [ "${r}" != "success" ] && [ "${r}" != "skipped" ]; then FAIL=1; fi
done
exit $FAIL
python/sglang/test/ascend/e2e/test_npu_performance_utils.py
+3
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@@ -183,6 +183,9 @@ QWEN3_5_397B_W8A8_MODEL_PATH = (
DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH = (
"/root/.cache/modelscope/hub/models/Eco-Tech/DeepSeek-V4-Flash-0731-w8a8"
)
DEEPSEEK_V4_FLASH_DEFAULT_MODEL_PATH = (
"/root/.cache/modelscope/hub/models/deepseek-ai/DeepSeek-V4-Flash"
)
QWEN3_5_397B_W4A8_MODEL_PATH = (
"/root/.cache/modelscope/hub/models/Eco-Tech/Qwen3.5-397B-A17B-w4a8-mtp"
)
test/registered/npu/accuracy/deepseek_v4_flash/test_npu_deepseek_v4_flash_fp8_4p_gpqa_a5.py
+143
View File
@@ -0,0 +1,143 @@
import unittest
from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
BENCHMARK_TOOL_DEFAULT,
TestNpuAccuracyTestCaseBase,
)
from sglang.test.ascend.e2e.test_npu_performance_utils import (
DEEPSEEK_V4_FLASH_DEFAULT_MODEL_PATH,
)
from sglang.test.ci.ci_register import register_npu_ci
register_npu_ci(
est_time=7200,
suite="nightly-acc-4-npu-a5",
nightly=True,
)
DEEPSEEK_V4_FLASH_FP8_4P_ENVS = {
"PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
"STREAMS_PER_DEVICE": "32",
"SGLANG_SET_CPU_AFFINITY": "1",
"TASK_QUEUE_ENABLE": "1",
"INF_NAN_MODE_FORCE_DISABLE": "1",
"SGLANG_DEFAULT_THINKING": "1",
"SGLANG_DSV4_REASONING_EFFORT": "max",
# HCCL deepep
"HCCL_BUFFSIZE": "1024",
"HCCL_SOCKET_IFNAME": "lo",
"GLOO_SOCKET_IFNAME": "lo",
# DeepEP long-sequence normal combine (ROUND * TOKENS >= chunked_prefill_size / tp * dp)
"DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ": "1",
"DEEPEP_NORMAL_LONG_SEQ_ROUND": "16",
"DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS": "2048",
# "DEEPEP_HYBRID_DEPLOYMENT": "1",
# dsv4
"IS_DEEPSEEK_V4": "1",
"USE_FUSED_HC_PRE_ASCENDC": "1",
"SGLANG_DSV4_NPU_FUSED_COMPRESSOR": "1",
"SGLANG_DSV4_NPU_FUSED_COMPRESSOR_PREFILL": "1",
# skip gpu branch
"SGLANG_OPT_USE_OVERLAP_STORE_CACHE": "False",
"FORCE_DRAFT_MODEL_NON_QUANT": "1",
"SGLANG_DSV4_FP4_EXPERTS": "True",
"SGLANG_OPT_FUSE_WQA_WKV": "0",
"SGLANG_OPT_BF16_FP32_GEMM_ALGO": "torch",
"SGLANG_OPT_USE_FUSED_HASH_TOPK": "False",
"SGLANG_OPT_USE_TILELANG_MHC_PRE": "False",
"SGLANG_OPT_DEEPGEMM_HC_PRENORM": "False",
"SGLANG_OPT_USE_TILELANG_MHC_POST": "False",
"SGLANG_OPT_FP8_WO_A_GEMM": "False",
# performance
"SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
"SGLANG_NPU_USE_MULTI_STREAM": "1",
"USE_NPU_MOE_GATING_TOP_K": "1",
"SGLANG_PROFILE_WITH_STACK": "False",
}
DEEPSEEK_V4_FLASH_FP8_4P_OTHER_ARGS = [
"--page-size",
128,
"--tp-size",
4,
"--trust-remote-code",
"--attention-backend",
"dsv4",
"--device",
"npu",
"--watchdog-timeout",
9000,
"--mem-fraction-static",
0.72,
"--max-running-requests",
64,
"--chunked-prefill-size",
131072,
"--max-prefill-tokens",
131072,
"--cuda-graph-bs-decode",
1,
2,
4,
8,
10,
16,
"--kv-cache-dtype",
"auto",
"--enable-dp-lm-head",
"--disable-radix-cache",
"--enable-dp-attention",
"--dp-size",
4,
"--reasoning-parser",
"deepseek-v4",
"--speculative-algorithm",
"EAGLE",
"--speculative-num-steps",
2,
"--speculative-eagle-topk",
1,
"--speculative-num-draft-tokens",
3,
"--quantization",
"fp8",
"--moe-a2a-backend",
"deepep",
"--deepep-mode",
"auto",
]
DEEPSEEK_V4_FLASH_FP8_4P_GENERATION_CONFIG_MAX = {
"max_tokens": 125000,
"top_p": 1,
"temperature": 1,
"n": 1,
"extra_body": {
"chat_template_kwargs": {"thinking": True, "reasoning_effort": "max"}
},
}
class TestNPUDeepSeekV4FlashFP84PGPQA(TestNpuAccuracyTestCaseBase):
"""Test NPU accuracy for DeepSeek-V4-Flash FP8 4p EAGLE GPQA."""
benchmark_tool = BENCHMARK_TOOL_DEFAULT
model = DEEPSEEK_V4_FLASH_DEFAULT_MODEL_PATH
other_args = DEEPSEEK_V4_FLASH_FP8_4P_OTHER_ARGS
envs = DEEPSEEK_V4_FLASH_FP8_4P_ENVS
accuracy = 0.874
datasets = ["gpqa_diamond"]
few_shot_num = 0
generation_config = DEEPSEEK_V4_FLASH_FP8_4P_GENERATION_CONFIG_MAX
eval_batch_size = 128
stream = True
timeout = 6000
seed = 1
def test_npu_deepseek_v4_flash_fp8_4p_gpqa(self):
"""Run NPU accuracy test for DeepSeek-V4-Flash FP8 4p EAGLE GPQA."""
self.run_accuracy()
if __name__ == "__main__":
unittest.main()
test/registered/npu/accuracy/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_gpqa.py
+6
View File
@@ -15,6 +15,12 @@ register_npu_ci(
nightly=True,
)
register_npu_ci(
est_time=7200,
suite="nightly-acc-16-npu-a3-cann910",
nightly=True,
)
DEEPSEEK_V4_FLASH_W8A8_DSPARK_8P_ENVS = {
"PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
"STREAMS_PER_DEVICE": "32",
test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in32k_out1k_50ms.py
-132
View File
@@ -1,132 +0,0 @@
import unittest
from sglang.test.ascend.e2e.test_npu_performance_utils import (
AISBENCHMARK_DATASET_DEFAULT,
BENCHMARK_TOOL_DEFAULT,
DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
TestNpuPerformanceTestCaseBase,
)
from sglang.test.ci.ci_register import register_npu_ci
register_npu_ci(est_time=1800, suite="nightly-perf-16-npu-a3", nightly=True)
# Environment variables for DSV4-Flash single-node PD-mix deployment.
DEEPSEEK_V4_FLASH_W8A8_8P_ENVS = {
"PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
"STREAMS_PER_DEVICE": "32",
"INF_NAN_MODE_FORCE_DISABLE": "1",
"SGLANG_SET_CPU_AFFINITY": "1",
"HCCL_SOCKET_IFNAME": "lo",
"GLOO_SOCKET_IFNAME": "lo",
"HCCL_OP_EXPANSION_MODE": "AIV",
"USE_NPU_MOE_GATING_TOP_K": "1",
"SGLANG_NPU_USE_MULTI_STREAM": "1",
# deepep
"DEEP_NORMAL_MODE_USE_INT8_QUANT": "1",
"DEEPEP_HCCL_BUFFSIZE": "2048",
"SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "35",
"DEEPEP_HYBRID_DEPLOYMENT": "1",
# war barrier
"SGLANG_ENABLE_WAR_BARRIER": "1",
"SGLANG_FORCE_COARSE_WAR_BARRIER": "1",
# skip gpu branch
"SGLANG_OPT_FP8_WO_A_GEMM": "0",
"SGLANG_OPT_USE_OVERLAP_STORE_CACHE": "False",
"FORCE_DRAFT_MODEL_NON_QUANT": "1",
"SGLANG_DSV4_FP4_EXPERTS": "False",
"SGLANG_OPT_FUSE_WQA_WKV": "0",
"SGLANG_OPT_BF16_FP32_GEMM_ALGO": "torch",
"SGLANG_OPT_USE_FUSED_HASH_TOPK": "False",
"SGLANG_OPT_USE_TILELANG_MHC_PRE": "False",
"SGLANG_OPT_DEEPGEMM_HC_PRENORM": "False",
"SGLANG_OPT_USE_TILELANG_MHC_POST": "False",
# mtp
"SGLANG_ENABLE_SPEC_V2": "1",
"SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
}
# Server launch arguments for DSV4-Flash W8A8 single-node 8p PD-mix.
DEEPSEEK_V4_FLASH_W8A8_8P_OTHER_ARGS = [
"--page-size",
128,
"--tp-size",
16,
"--trust-remote-code",
"--device",
"npu",
"--prefill-max-requests",
32,
"--max-prefill-tokens",
80000,
"--attention-backend",
"dsv4",
"--watchdog-timeout",
9000,
"--mem-fraction-static",
0.68,
"--chunked-prefill-size",
131072,
"--max-running-requests",
64,
"--dp-size",
16,
"--enable-dp-attention",
"--moe-a2a-backend",
"deepep",
"--deepep-mode",
"auto",
"--quantization",
"modelslim",
"--enable-dp-lm-head",
"--kv-cache-dtype",
"bfloat16",
"--skip-server-warmup",
"--cuda-graph-bs-decode",
1,
2,
4,
8,
# MTP (EAGLE) configuration.
"--speculative-algorithm",
"EAGLE",
"--speculative-num-steps",
2,
"--speculative-eagle-topk",
1,
"--speculative-num-draft-tokens",
3,
"--ep-size",
16,
"--disable-radix-cache",
]
class TestNPUDeepSeekV4FlashW8A88PIn32kOut1k50ms(TestNpuPerformanceTestCaseBase):
"""Test NPU performance for DeepSeek-V4-Flash W8A8 8p in32k out1k."""
benchmark_tool = BENCHMARK_TOOL_DEFAULT
dataset_type = AISBENCHMARK_DATASET_DEFAULT
model = DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH
other_args = DEEPSEEK_V4_FLASH_W8A8_8P_OTHER_ARGS
envs = DEEPSEEK_V4_FLASH_W8A8_8P_ENVS
dataset_name = "random"
dataset_path = "/root/.cache/modelscope/hub/datasets/gsm8k_deepseekv4/cache0_32000/formal_run1_64_32000_cache0.json"
input_len = 32000
output_len = 1000
num_prompts = 64
max_concurrency = 64
random_range_ratio = 1
warmup_requests = 16
request_rate = float("inf")
seed = 1
tpot = 50
max_attempts = 3
output_token_throughput = 927
def test_npu_deepseek_v4_flash_w8a8_8p_in32k_out1k_50ms(self):
"""Run NPU performance test for DeepSeek-V4-Flash W8A8 8p in32k out1k."""
self.run_throughput()
if __name__ == "__main__":
unittest.main()
test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
+1
View File
@@ -9,6 +9,7 @@ from sglang.test.ascend.e2e.test_npu_performance_utils import (
from sglang.test.ci.ci_register import register_npu_ci
register_npu_ci(est_time=1800, suite="nightly-perf-16-npu-a3", nightly=True)
register_npu_ci(est_time=1800, suite="nightly-perf-16-npu-a3-cann910", nightly=True)
# Environment variables for DSV4-Flash single-node PD-mix deployment.
DEEPSEEK_V4_FLASH_W8A8_8P_ENVS = {
test/run_suite.py
+3
View File
@@ -170,9 +170,12 @@ NIGHTLY_SUITES = {
"nightly-acc-2-npu-a3",
"nightly-acc-8-npu-a3",
"nightly-acc-16-npu-a3",
"nightly-acc-4-npu-a5",
"nightly-perf-2-npu-a3",
"nightly-perf-4-npu-a3",
"nightly-perf-16-npu-a3",
"nightly-perf-16-npu-a3-cann910",
"nightly-acc-16-npu-a3-cann910",
"full-4-npu-a2",
"full-1-npu-a3",
"full-2-npu-a3",