[AMD][DI][CI] 5/N Add DSV4 wide-EP16 4-node 2P1D nightly recipes (#31500)
Co-authored-by: Chen <bingxche@amd.com>
This commit is contained in:
Zhaoyi Li
@@ -357,6 +357,149 @@ kimik26-fp8-mi355x-mtp-sglang:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp8/kimik26/1k1k/1p1d-mtp.yaml
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# AMD 4-node disaggregation with narrow-prefill EP8 + WIDE-decode EP16 (Oren's
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# 2P1D config: two single-node prefill engines EP8 that the router fans across +
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# one decode engine EP16 spanning 2 nodes; 4 nodes total). Runs on the `mi355x`
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# amd-sglang cluster (bnxt RoCE), not spur: spur's ionic fabric could not cross-
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# rail the MORI MoE all-to-all, so EP16 was brought up and validated on mi355x
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# (job 13221, DSV4-Pro-FP4, GSM8K 0.927). Each recipe sets
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# runtime.moe_a2a_backend=mori + runtime.kv_transfer_backend=mori +
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# runtime.ib_devices=rdma0..7 + runtime.dist_socket_ifname=eno0; launch_mi355x.sh
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# derives nodes-per-engine = ceil(TP/8) (prefill 8->1, decode 16->2) and emits the
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# cross-node --nnodes/--node-rank/--dist-init-addr args for the decode engine.
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# DSV4-Pro MTP drops conc256 (SWA retract->get_cpu_copy NotImplementedError).
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dsv4flash-fp8-mi355x-ep16-sglang:
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model: sgl-project/DeepSeek-V4-Flash-FP8
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model-prefix: dsv4flash
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model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Flash-FP8
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runner: mi355x
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precision: fp8
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4flash/1k1k/2p1d-ep16.yaml
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dsv4flash-fp8-mi355x-ep16-mtp-sglang:
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model: sgl-project/DeepSeek-V4-Flash-FP8
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model-prefix: dsv4flash
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model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Flash-FP8
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runner: mi355x
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precision: fp8
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4flash/1k1k/2p1d-ep16-mtp.yaml
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dsv4pro-fp8-mi355x-ep16-sglang:
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model: sgl-project/DeepSeek-V4-Pro-FP8
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model-prefix: dsv4pro
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model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Pro-FP8
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runner: mi355x
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precision: fp8
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4pro/1k1k/2p1d-ep16.yaml
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dsv4pro-fp8-mi355x-ep16-mtp-sglang:
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model: sgl-project/DeepSeek-V4-Pro-FP8
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model-prefix: dsv4pro
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model_path: /it-share/model_coverage/models--sgl-project--DeepSeek-V4-Pro-FP8
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runner: mi355x
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precision: fp8
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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# conc256 excluded: disagg-decode SWA hybrid pool retract->get_cpu_copy
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# is an upstream NotImplementedError (crashes decode). See recipe.
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- conc-list: [1, 8, 16, 32, 64, 128]
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config_file: scripts/ci/slurm/recipes/mi355x-fp8/dsv4pro/1k1k/2p1d-ep16-mtp.yaml
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dsv4flash-fp4-mi355x-ep16-sglang:
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model: deepseek-ai/DeepSeek-V4-Flash
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model-prefix: dsv4flash
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model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Flash
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runner: mi355x
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precision: fp4
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4flash/1k1k/2p1d-ep16.yaml
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dsv4flash-fp4-mi355x-ep16-mtp-sglang:
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model: deepseek-ai/DeepSeek-V4-Flash
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model-prefix: dsv4flash
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model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Flash
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runner: mi355x
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precision: fp4
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4flash/1k1k/2p1d-ep16-mtp.yaml
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dsv4pro-fp4-mi355x-ep16-sglang:
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model: deepseek-ai/DeepSeek-V4-Pro
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model-prefix: dsv4pro
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model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Pro
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runner: mi355x
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precision: fp4
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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- conc-list: [1, 8, 16, 32, 64, 128, 256]
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config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4pro/1k1k/2p1d-ep16.yaml
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dsv4pro-fp4-mi355x-ep16-mtp-sglang:
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model: deepseek-ai/DeepSeek-V4-Pro
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model-prefix: dsv4pro
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model_path: /it-share/model_coverage/models--deepseek-ai--DeepSeek-V4-Pro
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runner: mi355x
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precision: fp4
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framework: sglang
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multinode: true
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disagg: true
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seq-len-configs:
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- isl: 1024
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osl: 1024
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search-space:
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# conc256 excluded: disagg-decode SWA hybrid pool retract->get_cpu_copy
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# is an upstream NotImplementedError (crashes decode). See recipe.
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- conc-list: [1, 8, 16, 32, 64, 128]
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config_file: scripts/ci/slurm/recipes/mi355x-fp4/dsv4pro/1k1k/2p1d-ep16-mtp.yaml
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# Kimi-K2.6 MXFP4 wide-EP16 2P1D: aiter MoE path, needs only the wide-EP launcher, not #32048.
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kimik26-mxfp4-mi355x-ep16-sglang:
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model: amd/Kimi-K2.6-MXFP4
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@@ -0,0 +1,107 @@
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# MI355X DeepSeek-V4-Flash FP4 4-node 2P1D disaggregation recipe — narrow-prefill EP8 + MTP
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# + wide-decode EP16 (Oren's config: wide EP only helps decode).
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#
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# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
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# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
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# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
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# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
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# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
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# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
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# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
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# latent, not head-sharded), and is carried over mori.
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#
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# Consumed by:
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# * scripts/ci/slurm/process_result.py reads `resources` and
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# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
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# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
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resources:
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prefill_workers: 2
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decode_workers: 1
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backend:
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sglang_config:
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prefill:
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tensor-parallel-size: 8
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expert-parallel-size: 8
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data-parallel-size: 8
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decode:
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tensor-parallel-size: 16
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expert-parallel-size: 16
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data-parallel-size: 16
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runtime:
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image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
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attention_backend: dsv4
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# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
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ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
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# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
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moe_a2a_backend: mori
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# KV P->D transfer backend (mori for both a2a and KV on this cluster).
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kv_transfer_backend: mori
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# Cross-node torch-distributed NIC for the wide decode engine's dist init.
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dist_socket_ifname: eno0
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# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
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rocm700a: 0
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prefill_port: 30025
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decode_port: 30026
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prefill_bootstrap_port: 8998
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decode_bootstrap_port: 9001
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lb_port: 8000
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# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
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mem_fraction_static: 0.90
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page_size: 256
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max_running_requests: 256
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chunked_prefill_size: 131072
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swa_full_tokens_ratio: 0.1
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# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
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# differ, so these split what the single-node EP<=8 recipes leave symmetric.
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wide_ep:
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kv_cache_dtype: fp8_e4m3
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prefill_mem_fraction_static: 0.8
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decode_mem_fraction_static: 0.85
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prefill_chunked_prefill_size: 131072
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prefill_max_running_requests: 1024
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decode_max_running_requests: 1024
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common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
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prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
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# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
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# region over 4 GiB and mori registers each KV buffer as one region
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# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
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# ceiling is 16,777,216 tokens; MTP runs at 7,000,000 (the validated value,
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# well under the ceiling and below every MTP leg's natural pool).
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decode_extra_flags: "--max-total-tokens 7000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
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prefill_extra_env:
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MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
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MORI_MAX_DISPATCH_TOKENS_DECODE: 256
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SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
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# MTP decode capture drives the MoE dispatch to cuda_graph_bs * draft_tokens
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# tokens/rank, so the decode buffers must clear that; 512/2048/1024 validated
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# on mi355x (undersized values abort during decode cuda-graph capture).
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decode_extra_env:
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MORI_MAX_DISPATCH_TOKENS_DECODE: 512
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MORI_MOE_MAX_INPUT_TOKENS_DECODE: 2048
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SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 1024
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# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
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# both prefill and decode.
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mtp:
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enabled: true
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num_steps: 3
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eagle_topk: 1
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num_draft_tokens: 4
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bench:
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# bench_serving --max-concurrency sweep; one result JSON per concurrency.
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concurrencies: [1, 8, 16, 32, 64, 128, 256]
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num_prompts_factor: 4 # num-prompts = concurrency * factor
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random_range_ratio: 1.0
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# Correctness gate run through the PD path before the perf sweep (full GSM8K,
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# 8-shot, accuracy > 0.91). A regression here fails the nightly even when
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# throughput looks fine ("fast but wrong").
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accuracy:
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enabled: true
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num_shots: 8
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num_questions: 1319 # full GSM8K test set
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threshold: 0.91
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@@ -0,0 +1,95 @@
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# MI355X DeepSeek-V4-Flash FP4 4-node 2P1D disaggregation recipe — narrow-prefill EP8
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# Consumed by:
|
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# * scripts/ci/slurm/process_result.py reads `resources` and
|
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# `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
|
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# * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, and `mtp`.
|
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resources:
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prefill_workers: 2
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decode_workers: 1
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backend:
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sglang_config:
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prefill:
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tensor-parallel-size: 8
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expert-parallel-size: 8
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data-parallel-size: 8
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decode:
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tensor-parallel-size: 16
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expert-parallel-size: 16
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data-parallel-size: 16
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runtime:
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image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
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attention_backend: dsv4
|
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# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
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ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
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# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
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rocm700a: 0
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prefill_port: 30025
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decode_port: 30026
|
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prefill_bootstrap_port: 8998
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decode_bootstrap_port: 9001
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lb_port: 8000
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# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
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page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.8
|
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decode_mem_fraction_static: 0.85
|
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prefill_chunked_prefill_size: 131072
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||||
prefill_max_running_requests: 1024
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decode_max_running_requests: 1024
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common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; 16,000,000 leaves headroom.
|
||||
decode_extra_flags: "--max-total-tokens 16000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
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prefill_extra_env:
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MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
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MORI_MAX_DISPATCH_TOKENS_DECODE: 256
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SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
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decode_extra_env:
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MORI_MAX_DISPATCH_TOKENS_DECODE: 64
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MORI_MOE_MAX_INPUT_TOKENS_DECODE: 332
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SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 128
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bench:
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# 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:
|
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enabled: true
|
||||
num_shots: 8
|
||||
num_questions: 1319 # full GSM8K test set
|
||||
threshold: 0.91
|
||||
@@ -0,0 +1,107 @@
|
||||
# MI355X DeepSeek-V4-Pro FP4 4-node 2P1D disaggregation recipe — narrow-prefill EP8 + MTP
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# 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: 2
|
||||
decode_workers: 1
|
||||
|
||||
backend:
|
||||
sglang_config:
|
||||
prefill:
|
||||
tensor-parallel-size: 8
|
||||
expert-parallel-size: 8
|
||||
data-parallel-size: 8
|
||||
decode:
|
||||
tensor-parallel-size: 16
|
||||
expert-parallel-size: 16
|
||||
data-parallel-size: 16
|
||||
|
||||
runtime:
|
||||
image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
||||
attention_backend: dsv4
|
||||
# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
||||
ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
||||
# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
||||
rocm700a: 0
|
||||
prefill_port: 30025
|
||||
decode_port: 30026
|
||||
prefill_bootstrap_port: 8998
|
||||
decode_bootstrap_port: 9001
|
||||
lb_port: 8000
|
||||
# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
||||
page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.8
|
||||
decode_mem_fraction_static: 0.85
|
||||
prefill_chunked_prefill_size: 131072
|
||||
prefill_max_running_requests: 1024
|
||||
decode_max_running_requests: 1024
|
||||
common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; MTP runs at 7,000,000 (the validated value,
|
||||
# well under the ceiling and below every MTP leg's natural pool).
|
||||
decode_extra_flags: "--max-total-tokens 7000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
|
||||
prefill_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 256
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
|
||||
# MTP decode capture drives the MoE dispatch to cuda_graph_bs * draft_tokens
|
||||
# tokens/rank, so the decode buffers must clear that; 512/2048/1024 validated
|
||||
# on mi355x (undersized values abort during decode cuda-graph capture).
|
||||
decode_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 512
|
||||
MORI_MOE_MAX_INPUT_TOKENS_DECODE: 2048
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 1024
|
||||
|
||||
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
|
||||
# both prefill and decode.
|
||||
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 +1,95 @@
|
||||
# MI355X DeepSeek-V4-Pro FP4 4-node 2P1D disaggregation recipe — narrow-prefill EP8
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# 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: 2
|
||||
decode_workers: 1
|
||||
|
||||
backend:
|
||||
sglang_config:
|
||||
prefill:
|
||||
tensor-parallel-size: 8
|
||||
expert-parallel-size: 8
|
||||
data-parallel-size: 8
|
||||
decode:
|
||||
tensor-parallel-size: 16
|
||||
expert-parallel-size: 16
|
||||
data-parallel-size: 16
|
||||
|
||||
runtime:
|
||||
image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
||||
attention_backend: dsv4
|
||||
# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
||||
ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
||||
# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
||||
rocm700a: 0
|
||||
prefill_port: 30025
|
||||
decode_port: 30026
|
||||
prefill_bootstrap_port: 8998
|
||||
decode_bootstrap_port: 9001
|
||||
lb_port: 8000
|
||||
# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
||||
page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.8
|
||||
decode_mem_fraction_static: 0.85
|
||||
prefill_chunked_prefill_size: 131072
|
||||
prefill_max_running_requests: 1024
|
||||
decode_max_running_requests: 1024
|
||||
common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; 16,000,000 leaves headroom.
|
||||
decode_extra_flags: "--max-total-tokens 16000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
|
||||
prefill_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 256
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
|
||||
decode_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 64
|
||||
MORI_MOE_MAX_INPUT_TOKENS_DECODE: 332
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 128
|
||||
|
||||
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 +1,107 @@
|
||||
# MI355X DeepSeek-V4-Flash FP8 4-node 2P1D disaggregation recipe — narrow-prefill EP8 + MTP
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# 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: 2
|
||||
decode_workers: 1
|
||||
|
||||
backend:
|
||||
sglang_config:
|
||||
prefill:
|
||||
tensor-parallel-size: 8
|
||||
expert-parallel-size: 8
|
||||
data-parallel-size: 8
|
||||
decode:
|
||||
tensor-parallel-size: 16
|
||||
expert-parallel-size: 16
|
||||
data-parallel-size: 16
|
||||
|
||||
runtime:
|
||||
image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
||||
attention_backend: dsv4
|
||||
# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
||||
ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
||||
# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
||||
rocm700a: 0
|
||||
prefill_port: 30025
|
||||
decode_port: 30026
|
||||
prefill_bootstrap_port: 8998
|
||||
decode_bootstrap_port: 9001
|
||||
lb_port: 8000
|
||||
# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
||||
page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.8
|
||||
decode_mem_fraction_static: 0.85
|
||||
prefill_chunked_prefill_size: 131072
|
||||
prefill_max_running_requests: 1024
|
||||
decode_max_running_requests: 1024
|
||||
common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; MTP runs at 7,000,000 (the validated value,
|
||||
# well under the ceiling and below every MTP leg's natural pool).
|
||||
decode_extra_flags: "--max-total-tokens 7000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
|
||||
prefill_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 256
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
|
||||
# MTP decode capture drives the MoE dispatch to cuda_graph_bs * draft_tokens
|
||||
# tokens/rank, so the decode buffers must clear that; 512/2048/1024 validated
|
||||
# on mi355x (undersized values abort during decode cuda-graph capture).
|
||||
decode_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 512
|
||||
MORI_MOE_MAX_INPUT_TOKENS_DECODE: 2048
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 1024
|
||||
|
||||
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
|
||||
# both prefill and decode.
|
||||
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 +1,95 @@
|
||||
# MI355X DeepSeek-V4-Flash FP8 4-node 2P1D disaggregation recipe — narrow-prefill EP8
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# 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: 2
|
||||
decode_workers: 1
|
||||
|
||||
backend:
|
||||
sglang_config:
|
||||
prefill:
|
||||
tensor-parallel-size: 8
|
||||
expert-parallel-size: 8
|
||||
data-parallel-size: 8
|
||||
decode:
|
||||
tensor-parallel-size: 16
|
||||
expert-parallel-size: 16
|
||||
data-parallel-size: 16
|
||||
|
||||
runtime:
|
||||
image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
||||
attention_backend: dsv4
|
||||
# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
||||
ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
||||
# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
||||
rocm700a: 0
|
||||
prefill_port: 30025
|
||||
decode_port: 30026
|
||||
prefill_bootstrap_port: 8998
|
||||
decode_bootstrap_port: 9001
|
||||
lb_port: 8000
|
||||
# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
||||
page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.8
|
||||
decode_mem_fraction_static: 0.85
|
||||
prefill_chunked_prefill_size: 131072
|
||||
prefill_max_running_requests: 1024
|
||||
decode_max_running_requests: 1024
|
||||
common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; 16,000,000 leaves headroom.
|
||||
decode_extra_flags: "--max-total-tokens 16000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
|
||||
prefill_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 256
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
|
||||
decode_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 64
|
||||
MORI_MOE_MAX_INPUT_TOKENS_DECODE: 332
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 128
|
||||
|
||||
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 +1,107 @@
|
||||
# MI355X DeepSeek-V4-Pro FP8 4-node 2P1D disaggregation recipe — narrow-prefill EP8 + MTP
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# 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: 2
|
||||
decode_workers: 1
|
||||
|
||||
backend:
|
||||
sglang_config:
|
||||
prefill:
|
||||
tensor-parallel-size: 8
|
||||
expert-parallel-size: 8
|
||||
data-parallel-size: 8
|
||||
decode:
|
||||
tensor-parallel-size: 16
|
||||
expert-parallel-size: 16
|
||||
data-parallel-size: 16
|
||||
|
||||
runtime:
|
||||
image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
||||
attention_backend: dsv4
|
||||
# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
||||
ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
||||
# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
||||
rocm700a: 0
|
||||
prefill_port: 30025
|
||||
decode_port: 30026
|
||||
prefill_bootstrap_port: 8998
|
||||
decode_bootstrap_port: 9001
|
||||
lb_port: 8000
|
||||
# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
||||
page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.85
|
||||
decode_mem_fraction_static: 0.85
|
||||
prefill_chunked_prefill_size: 131072
|
||||
prefill_max_running_requests: 1024
|
||||
decode_max_running_requests: 1024
|
||||
common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; MTP runs at 7,000,000 (the validated value,
|
||||
# well under the ceiling and below every MTP leg's natural pool).
|
||||
decode_extra_flags: "--max-total-tokens 7000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
|
||||
prefill_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 256
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
|
||||
# MTP decode capture drives the MoE dispatch to cuda_graph_bs * draft_tokens
|
||||
# tokens/rank, so the decode buffers must clear that; 512/2048/1024 validated
|
||||
# on mi355x (undersized values abort during decode cuda-graph capture).
|
||||
decode_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 512
|
||||
MORI_MOE_MAX_INPUT_TOKENS_DECODE: 2048
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 1024
|
||||
|
||||
# MTP / EAGLE speculative decoding (NextN head from the base model). Applied to
|
||||
# both prefill and decode.
|
||||
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 +1,95 @@
|
||||
# MI355X DeepSeek-V4-Pro FP8 4-node 2P1D disaggregation recipe — narrow-prefill EP8
|
||||
# + wide-decode EP16 (Oren's config: wide EP only helps decode).
|
||||
#
|
||||
# Two prefill engines (EP8, one node each; the router fans requests across both) +
|
||||
# one decode engine (EP16) spanning 2 nodes. Still one logical P/D pair per role
|
||||
# group, 4 nodes total. nodes-per-engine = ceil(TP/8): prefill 8->1, decode 16->2,
|
||||
# so the launcher emits cross-node --nnodes/--node-rank/--dist-init-addr for the
|
||||
# decode engine only. Prefill EP8 keeps MoE all-to-all INTRA-node (XGMI, known
|
||||
# good); decode gets wide EP16 across nodes. Mismatched-TP KV (prefill TP8 ->
|
||||
# decode TP16) is layout-compatible for DeepSeek MLA (KV is a replicated per-token
|
||||
# latent, not head-sharded), and is carried over mori.
|
||||
#
|
||||
# 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: 2
|
||||
decode_workers: 1
|
||||
|
||||
backend:
|
||||
sglang_config:
|
||||
prefill:
|
||||
tensor-parallel-size: 8
|
||||
expert-parallel-size: 8
|
||||
data-parallel-size: 8
|
||||
decode:
|
||||
tensor-parallel-size: 16
|
||||
expert-parallel-size: 16
|
||||
data-parallel-size: 16
|
||||
|
||||
runtime:
|
||||
image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260715
|
||||
attention_backend: dsv4
|
||||
# RoCE HCAs (8/node) for mori MoE all-to-all AND the P->D KV transfer.
|
||||
ib_devices: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
|
||||
# Wide-EP MoE all-to-all backend (cross-node expert dispatch/combine).
|
||||
moe_a2a_backend: mori
|
||||
# KV P->D transfer backend (mori for both a2a and KV on this cluster).
|
||||
kv_transfer_backend: mori
|
||||
# Cross-node torch-distributed NIC for the wide decode engine's dist init.
|
||||
dist_socket_ifname: eno0
|
||||
# rocm720 0715 image needs the ROCm-7.0.0-alpha path OFF (validated).
|
||||
rocm700a: 0
|
||||
prefill_port: 30025
|
||||
decode_port: 30026
|
||||
prefill_bootstrap_port: 8998
|
||||
decode_bootstrap_port: 9001
|
||||
lb_port: 8000
|
||||
# Base defaults; the wide_ep block overrides mem-fraction / max-req per role.
|
||||
mem_fraction_static: 0.90
|
||||
page_size: 256
|
||||
max_running_requests: 256
|
||||
chunked_prefill_size: 131072
|
||||
swa_full_tokens_ratio: 0.1
|
||||
# Per-role wide-EP tuning (validated 2P1D run, job 13196). Prefill and decode
|
||||
# differ, so these split what the single-node EP<=8 recipes leave symmetric.
|
||||
wide_ep:
|
||||
kv_cache_dtype: fp8_e4m3
|
||||
prefill_mem_fraction_static: 0.8
|
||||
decode_mem_fraction_static: 0.85
|
||||
prefill_chunked_prefill_size: 131072
|
||||
prefill_max_running_requests: 1024
|
||||
decode_max_running_requests: 1024
|
||||
common_extra_flags: "--moe-dense-tp-size 1 --enable-dp-lm-head --decode-log-interval 100 --watchdog-timeout 3600 --load-balance-method round_robin"
|
||||
prefill_extra_flags: "--context-length 9217 --max-total-tokens 262144"
|
||||
# Cap the decode KV pool: the ionic NIC rejects any single RDMA memory
|
||||
# region over 4 GiB and mori registers each KV buffer as one region
|
||||
# (no chunking). Largest buffer = max_total_num_tokens * 256 B, so the
|
||||
# ceiling is 16,777,216 tokens; 16,000,000 leaves headroom.
|
||||
decode_extra_flags: "--max-total-tokens 16000000 --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 --prefill-round-robin-balance"
|
||||
prefill_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_PREFILL: 8192
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 256
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 16384
|
||||
decode_extra_env:
|
||||
MORI_MAX_DISPATCH_TOKENS_DECODE: 64
|
||||
MORI_MOE_MAX_INPUT_TOKENS_DECODE: 332
|
||||
SGLANG_MORI_NUM_MAX_DISPATCH_TOKENS_PER_RANK: 128
|
||||
|
||||
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
|
||||
Reference in New Issue
Block a user