[AMD][DI][CI] 2/N Add DSV4 DP8/EP8 and MTP MI355X 1P1D nightly recipes (#29784)

Co-authored-by: bingxche <bingxche@amd.com>
This commit is contained in:
Zhaoyi Li
2026-07-01 23:46:48 +08:00
committed by GitHub
co-authored by bingxche
parent 2a6e5c60fe
commit 9bb7de9258
15 changed files with 970 additions and 3 deletions
@@ -142,8 +142,40 @@ jobs:
# Manual dispatch input wins; otherwise use the latest image resolved
# by the setup job; otherwise the launcher falls back to the recipe default.
IMAGE_OVERRIDE: ${{ inputs.image != '' && inputs.image || needs.setup.outputs.image }}
# Keep the scheduler off mia1-p01-g20: its ionic RDMA driver ABI
# mismatches the container, so MORI reports "no active RDMA device"
# and the disagg server dies on init. Remove once the node is fixed.
SLURM_EXCLUDE: mia1-p01-g20
run: bash scripts/ci/slurm/launch_mi355x.sh
- name: Pack logs
if: always()
run: |
LOG_DIR="$HOME/.mi355x_ci/${MATRIX_CONFIG_NAME}"
LOG_BUNDLE="${GITHUB_WORKSPACE}/${RESULT_FILENAME}_logs.tar.gz"
if [ ! -d "$LOG_DIR" ]; then
echo "WARN: log directory not found: $LOG_DIR"
exit 0
fi
mapfile -d '' LOG_FILES < <(
find "$LOG_DIR" -maxdepth 1 -type f \
\( -name '*.log' -o -name 'server_exit_*' -o -name 'bench_exit' \) \
-printf '%P\0' | sort -z
)
if [ "${#LOG_FILES[@]}" -eq 0 ]; then
echo "WARN: no log files found in $LOG_DIR"
exit 0
fi
STAGING_DIR="$(mktemp -d)"
trap 'rm -rf "$STAGING_DIR"' EXIT
for log_file in "${LOG_FILES[@]}"; do
cp -a "$LOG_DIR/$log_file" "$STAGING_DIR/$log_file" || true
done
tar czf "$LOG_BUNDLE" -C "$STAGING_DIR" .
echo "Packed ${#LOG_FILES[@]} log file(s) -> $LOG_BUNDLE"
- name: Process results
if: always()
run: |
@@ -164,7 +196,9 @@ jobs:
uses: actions/upload-artifact@v4
with:
name: mi355x-${{ matrix.config.name }}-${{ github.run_id }}
path: ${{ github.workspace }}/*.json
path: |
${{ github.workspace }}/*.json
${{ github.workspace }}/*_logs.tar.gz
retention-days: 30
if-no-files-found: warn
+29 -2
View File
@@ -22,6 +22,8 @@
# MODEL_PATH - local snapshot dir (preferred over downloading MODEL)
# SLURM_PARTITION - default: amd-sglang
# SLURM_NODELIST - optional explicit node pin (else scheduler chooses)
# SLURM_EXCLUDE - optional comma-separated nodes to keep the scheduler
# off (e.g. hosts with a broken RDMA driver)
# RUNNER_NAME - GitHub runner name (a built-in default env var)
# GITHUB_RUN_ID - GitHub Actions run id (a built-in default env var)
# The allocation is named
@@ -101,6 +103,13 @@ emit("CHUNK", rt["chunked_prefill_size"])
emit("SWA", rt["swa_full_tokens_ratio"])
emit("PTP", b["prefill"]["tensor-parallel-size"])
emit("DTP", b["decode"]["tensor-parallel-size"])
emit("PEP", b["prefill"].get("expert-parallel-size", 1))
emit("PDP", b["prefill"].get("data-parallel-size", 1))
m = r.get("mtp", {}) or {}
emit("MTP_ENABLED", 1 if m.get("enabled") else 0)
emit("MTP_STEPS", m.get("num_steps", 3))
emit("MTP_TOPK", m.get("eagle_topk", 1))
emit("MTP_DRAFT", m.get("num_draft_tokens", 4))
# Worker counts double as node counts here: one server per node (TP == GPUs/node).
# 1P1D today; bumping these reserves 2P2D / 1P3D / 3P1D. Multi-node-per-worker
# (TP > GPUs/node, needs --dist-init-addr/--nnodes/--node-rank) is out of scope.
@@ -175,12 +184,24 @@ DSV4_ENV=(
DSV4_ENV_STR="${DSV4_ENV[*]}"
MORI_ENV="-e MORI_DISABLE_AUTO_XGMI=1 -e NCCL_IB_HCA=ionic -e NCCL_IB_GID_INDEX=1 -e NCCL_CROSS_NIC=1"
# Optional topology / speculative-decode flags driven by the recipe. Base recipes
# (EP1/DP1, no mtp) leave EXTRA_FLAGS empty, preserving prior behavior exactly.
EXTRA_FLAGS=""
(( PDP > 1 )) && EXTRA_FLAGS="$EXTRA_FLAGS --enable-dp-attention --dp-size $PDP"
(( PEP > 1 )) && EXTRA_FLAGS="$EXTRA_FLAGS --ep-size $PEP"
if [[ "$MTP_ENABLED" == "1" ]]; then
EXTRA_FLAGS="$EXTRA_FLAGS --speculative-algorithm EAGLE \
--speculative-num-steps $MTP_STEPS --speculative-eagle-topk $MTP_TOPK \
--speculative-num-draft-tokens $MTP_DRAFT"
fi
echo "extra flags: ${EXTRA_FLAGS:-<none>} (pep=$PEP pdp=$PDP mtp=$MTP_ENABLED)"
COMMON_FLAGS="--trust-remote-code --tp $PTP --disable-radix-cache \
--attention-backend $ATTN --max-running-requests $MAXREQ --page-size $PAGE \
--mem-fraction-static $MEMFRAC --swa-full-tokens-ratio $SWA \
--chunked-prefill-size $CHUNK --disable-shared-experts-fusion \
--tool-call-parser deepseekv4 --reasoning-parser deepseek-v4 \
--disaggregation-transfer-backend mori --disaggregation-ib-device $IB"
--disaggregation-transfer-backend mori --disaggregation-ib-device $IB$EXTRA_FLAGS"
DOCKER_COMMON="--rm --network host --ipc host --shm-size 32g --privileged \
--security-opt seccomp=unconfined \
@@ -367,6 +388,12 @@ NODELIST_ARG=()
EXCLUSIVE_ARG=()
[[ "${SLURM_EXCLUSIVE:-1}" == "1" ]] && EXCLUSIVE_ARG=(--exclusive)
# Keep the scheduler off known-bad nodes (e.g. a host whose ionic RDMA driver
# ABI mismatches the container, where MORI reports "no active RDMA device" and
# the disagg server dies on init). Comma-separated node list.
EXCLUDE_ARG=()
[[ -n "${SLURM_EXCLUDE:-}" ]] && EXCLUDE_ARG=(--exclude="$SLURM_EXCLUDE")
# One node per prefill/decode worker (TP == GPUs/node). 1P1D -> 2 nodes.
TOTAL_NODES=$((PW + DW))
@@ -377,7 +404,7 @@ TOTAL_NODES=$((PW + DW))
JOB_NAME="mi355x-ci-${RUNNER_NAME:-norunner}-${GITHUB_RUN_ID:-0}-${MATRIX_CONFIG_NAME}"
set +e
salloc -p "$SLURM_PARTITION" -N"$TOTAL_NODES" "${NODELIST_ARG[@]}" "${EXCLUSIVE_ARG[@]}" \
salloc -p "$SLURM_PARTITION" -N"$TOTAL_NODES" "${NODELIST_ARG[@]}" "${EXCLUDE_ARG[@]}" "${EXCLUSIVE_ARG[@]}" \
--job-name "$JOB_NAME" -t "$TIME_LIMIT" \
bash "$WORKDIR/drive.sh" "$WORKDIR" "$PW" "$DW"
SALLOC_RC=$?
+203
View File
@@ -117,3 +117,206 @@ dsv4pro-fp4-mi355x-sglang:
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4pro/1k1k/1p1d.yaml
# AMD MI355X 2-node 1P1D disaggregation over MORI with extra topology / MTP
# coverage on the SAME four DeepSeek-V4 model x precision combos as the base
# MORI blocks above (which stay TP8, no MTP). Three variants per model:
# * -mtp : TP8 + EAGLE MTP (recipe `mtp.enabled`)
# * -dp8ep8 : DP-attention 8 + narrow within-node EP8
# * -dp8ep8-mtp : DP8 + narrow EP8 + EAGLE MTP
# launch_mi355x.sh reads expert-/data-parallel-size and the `mtp:` section to
# append --ep-size / --enable-dp-attention --dp-size / --speculative-* flags.
dsv4flash-fp8-mi355x-mtp-sglang:
model: sgl-project/DeepSeek-V4-Flash-FP8
model-prefix: dsv4flash
model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Flash-FP8
runner: mi355x
precision: fp8
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4flash/1k1k/1p1d-mtp.yaml
dsv4flash-fp8-mi355x-dp8ep8-sglang:
model: sgl-project/DeepSeek-V4-Flash-FP8
model-prefix: dsv4flash
model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Flash-FP8
runner: mi355x
precision: fp8
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4flash/1k1k/1p1d-dp8ep8.yaml
dsv4flash-fp8-mi355x-dp8ep8-mtp-sglang:
model: sgl-project/DeepSeek-V4-Flash-FP8
model-prefix: dsv4flash
model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Flash-FP8
runner: mi355x
precision: fp8
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4flash/1k1k/1p1d-dp8ep8-mtp.yaml
dsv4pro-fp8-mi355x-mtp-sglang:
model: sgl-project/DeepSeek-V4-Pro-FP8
model-prefix: dsv4pro
model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Pro-FP8
runner: mi355x
precision: fp8
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
# conc256 excluded: disagg-decode SWA hybrid pool retract->get_cpu_copy
# is an upstream NotImplementedError (crashes decode). See recipe.
- conc-list: [1, 8, 16, 32, 64, 128]
config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4pro/1k1k/1p1d-mtp.yaml
dsv4pro-fp8-mi355x-dp8ep8-sglang:
model: sgl-project/DeepSeek-V4-Pro-FP8
model-prefix: dsv4pro
model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Pro-FP8
runner: mi355x
precision: fp8
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4pro/1k1k/1p1d-dp8ep8.yaml
dsv4pro-fp8-mi355x-dp8ep8-mtp-sglang:
model: sgl-project/DeepSeek-V4-Pro-FP8
model-prefix: dsv4pro
model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Pro-FP8
runner: mi355x
precision: fp8
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4pro/1k1k/1p1d-dp8ep8-mtp.yaml
dsv4flash-fp4-mi355x-mtp-sglang:
model: deepseek-ai/DeepSeek-V4-Flash
model-prefix: dsv4flash
model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Flash
runner: mi355x
precision: fp4
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4flash/1k1k/1p1d-mtp.yaml
dsv4flash-fp4-mi355x-dp8ep8-sglang:
model: deepseek-ai/DeepSeek-V4-Flash
model-prefix: dsv4flash
model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Flash
runner: mi355x
precision: fp4
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4flash/1k1k/1p1d-dp8ep8.yaml
dsv4flash-fp4-mi355x-dp8ep8-mtp-sglang:
model: deepseek-ai/DeepSeek-V4-Flash
model-prefix: dsv4flash
model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Flash
runner: mi355x
precision: fp4
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4flash/1k1k/1p1d-dp8ep8-mtp.yaml
dsv4pro-fp4-mi355x-mtp-sglang:
model: deepseek-ai/DeepSeek-V4-Pro
model-prefix: dsv4pro
model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Pro
runner: mi355x
precision: fp4
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4pro/1k1k/1p1d-mtp.yaml
dsv4pro-fp4-mi355x-dp8ep8-sglang:
model: deepseek-ai/DeepSeek-V4-Pro
model-prefix: dsv4pro
model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Pro
runner: mi355x
precision: fp4
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4pro/1k1k/1p1d-dp8ep8.yaml
dsv4pro-fp4-mi355x-dp8ep8-mtp-sglang:
model: deepseek-ai/DeepSeek-V4-Pro
model-prefix: dsv4pro
model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Pro
runner: mi355x
precision: fp4
framework: sglang
multinode: true
disagg: true
seq-len-configs:
- isl: 1024
osl: 1024
search-space:
- conc-list: [1, 8, 16, 32, 64, 128, 256]
config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4pro/1k1k/1p1d-dp8ep8-mtp.yaml
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Flash FP4 2-node 1P1D disaggregation recipe — DP8 + narrow EP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,52 @@
# MI355X DeepSeek-V4-Flash FP4 2-node 1P1D disaggregation recipe — DP8 + narrow EP8.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Flash FP4 2-node 1P1D disaggregation recipe — TP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
decode:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Pro FP4 2-node 1P1D disaggregation recipe — DP8 + narrow EP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,52 @@
# MI355X DeepSeek-V4-Pro FP4 2-node 1P1D disaggregation recipe — DP8 + narrow EP8.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Pro FP4 2-node 1P1D disaggregation recipe — TP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
decode:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Flash-FP8 2-node 1P1D disaggregation recipe — DP8 + narrow EP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,52 @@
# MI355X DeepSeek-V4-Flash-FP8 2-node 1P1D disaggregation recipe — DP8 + narrow EP8.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Flash-FP8 2-node 1P1D disaggregation recipe — TP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
decode:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,61 @@
# MI355X DeepSeek-V4-Pro-FP8 2-node 1P1D disaggregation recipe — DP8 + narrow EP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,52 @@
# MI355X DeepSeek-V4-Pro-FP8 2-node 1P1D disaggregation recipe — DP8 + narrow EP8.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
decode:
tensor-parallel-size: 8
expert-parallel-size: 8
data-parallel-size: 8
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
concurrencies: [1, 8, 16, 32, 64, 128, 256]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91
@@ -0,0 +1,68 @@
# MI355X DeepSeek-V4-Pro-FP8 2-node 1P1D disaggregation recipe — TP8 + MTP.
#
# Consumed by:
# * scripts/ci/slurm/process_result.py reads `resources` and
# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
resources:
prefill_workers: 1
decode_workers: 1
backend:
sglang_config:
prefill:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
decode:
tensor-parallel-size: 8
expert-parallel-size: 1
data-parallel-size: 1
runtime:
image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
attention_backend: dsv4
# RoCE HCAs MORI uses for cross-node KV transfer.
ib_devices: rdma0,rdma1,rdma2,rdma3
prefill_port: 30025
decode_port: 30026
prefill_bootstrap_port: 8998
decode_bootstrap_port: 9001
lb_port: 8000
mem_fraction_static: 0.90
page_size: 256
max_running_requests: 256
chunked_prefill_size: 8192
swa_full_tokens_ratio: 0.1
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
# both prefill and decode. Flags mirror
# test/registered/amd/test_deepseek_v4_pro_fp4_mtp.py.
mtp:
enabled: true
num_steps: 3
eagle_topk: 1
num_draft_tokens: 4
bench:
# bench_serving --max-concurrency sweep; one result JSON per concurrency.
# conc256 is excluded for this leg only: at conc256 the disagg-decode SWA
# hybrid KV pool fills, the scheduler retracts running requests, and the
# retract->offload_kv_cache path calls get_cpu_copy() which is unimplemented
# for the SWA hybrid pool (raises NotImplementedError, crashes the decode
# scheduler). Raising swa_full_tokens_ratio (tried up to 0.3) does not help
# -- usage climbs to fill the larger budget and still retracts. Until the
# upstream get_cpu_copy stub is implemented, cap this leg at 128.
concurrencies: [1, 8, 16, 32, 64, 128]
num_prompts_factor: 4 # num-prompts = concurrency * factor
random_range_ratio: 1.0
# Correctness gate run through the PD path before the perf sweep (full GSM8K,
# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
# throughput looks fine ("fast but wrong").
accuracy:
enabled: true
num_shots: 8
num_questions: 1319 # full GSM8K test set
threshold: 0.91