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Original file line number Diff line number Diff line change
@@ -0,0 +1,158 @@
# B200-FP8 GLM5 16k512 disaggregated recipe - HIGH THROUGHPUT candidates
# Preserve the proven 8k1k topology families while scaling token and KV limits for 16k512.

base:
name: "b200-fp8-glm5-dynamo-sglang"

model:
path: "glm5-fp8"
container: "nvcr.io/nvidia/ai-dynamo/sglang-runtime:1.4.0-inkling-dev.1"
precision: "fp8"

identity:
model:
repo: "zai-org/GLM-5-FP8"
revision: "4f96cc5eec29dcee5d6ded54f7ffe889438f9516"
container:
image: "nvcr.io/nvidia/ai-dynamo/sglang-runtime:1.4.0-inkling-dev.1"

resources:
gpu_type: "b200"
gpus_per_node: 8

frontend:
type: "dynamo"
args:
enforce-disagg: true
dynamo:
install: false
version: null

backend:
prefill_environment:
TORCH_DISTRIBUTED_DEFAULT_TIMEOUT: "1800"
PYTHONUNBUFFERED: "1"
DYN_SKIP_SGLANG_LOG_FORMATTING: "1"
SGLANG_DISAGGREGATION_HEARTBEAT_MAX_FAILURE: "100000"
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: "100000"
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: "100000"
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: "True"
SGLANG_USE_MESSAGE_QUEUE_BROADCASTER: "0"
NCCL_CUMEM_ENABLE: "1"
DYN_REQUEST_PLANE: "nats"

decode_environment:
TORCH_DISTRIBUTED_DEFAULT_TIMEOUT: "1800"
PYTHONUNBUFFERED: "1"
DYN_SKIP_SGLANG_LOG_FORMATTING: "1"
SGLANG_DISAGGREGATION_HEARTBEAT_MAX_FAILURE: "100000"
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: "100000"
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: "100000"
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: "True"
SGLANG_USE_MESSAGE_QUEUE_BROADCASTER: "0"
NCCL_CUMEM_ENABLE: "1"
DYN_REQUEST_PLANE: "nats"

sglang_config:
prefill:
# Model configuration
served-model-name: "GLM-5-FP8"
trust-remote-code: true
quantization: "fp8"
kv-cache-dtype: "fp8_e4m3"

# Disaggregation mode
disaggregation-mode: "prefill"
disaggregation-transfer-backend: "nixl"

# Size limits
max-running-requests: 160
cuda-graph-max-bs: 160
mem-fraction-static: 0.7
context-length: 16896
chunked-prefill-size: 131072
max-prefill-tokens: 16384

# Parallelism
tensor-parallel-size: 8
data-parallel-size: 8
expert-parallel-size: 1
enable-dp-attention: true
enable-dp-lm-head: true
load-balance-method: "total_tokens"

# Backend
nsa-decode-backend: "trtllm"
nsa-prefill-backend: "trtllm"
moe-runner-backend: "flashinfer_trtllm"

# Other flags
enable-flashinfer-allreduce-fusion: true
weight-loader-prefetch-checkpoints: true
disable-radix-cache: true
stream-interval: 30
model-loader-extra-config: '{"enable_multithread_load": true}'

decode:
# Model configuration
served-model-name: "GLM-5-FP8"
trust-remote-code: true

quantization: "fp8"
kv-cache-dtype: "fp8_e4m3"

# Disaggregation mode
disaggregation-mode: "decode"
disaggregation-transfer-backend: "nixl"

# Memory and token limits
mem-fraction-static: 0.8
context-length: 16896

# Parallelism
tensor-parallel-size: 8
expert-parallel-size: 1

# Backend
nsa-decode-backend: "trtllm"
nsa-prefill-backend: "trtllm"
moe-runner-backend: "flashinfer_trtllm"

# Other flags
enable-flashinfer-allreduce-fusion: true
weight-loader-prefetch-checkpoints: true
disable-radix-cache: true
stream-interval: 30
model-loader-extra-config: '{"enable_multithread_load": true}'

health_check:
max_attempts: 360
interval_seconds: 10

benchmark:
type: "sa-bench"
req_rate: "inf"

#### 16k512 throughput sweep: scaled from the 8k1k points ####

zip_override_16k512_hightpt:
resources:
prefill_nodes: [2, 1, 1]
prefill_workers: [2, 1, 1]
decode_nodes: [1, 1, 2]
decode_workers: [1, 1, 2]
backend:
sglang_config:
decode:
data-parallel-size: 8
enable-dp-lm-head: true
enable-dp-attention: true
load-balance-method: "total_tokens"

max-running-requests: [288, 224, 208]
cuda-graph-max-bs: [288, 224, 208]

benchmark:
isl: 16384
osl: 512
concurrencies: ["304", "240", "224"]
Original file line number Diff line number Diff line change
@@ -0,0 +1,154 @@
# B200-FP8 GLM5 16k512 disaggregated recipe - LOW LATENCY candidates

base:
name: "b200-fp8-glm5-dynamo-sglang"

model:
path: "glm5-fp8"
container: "nvcr.io/nvidia/ai-dynamo/sglang-runtime:1.4.0-inkling-dev.1"
precision: "fp8"

identity:
model:
repo: "zai-org/GLM-5-FP8"
revision: "4f96cc5eec29dcee5d6ded54f7ffe889438f9516"
container:
image: "nvcr.io/nvidia/ai-dynamo/sglang-runtime:1.4.0-inkling-dev.1"

resources:
gpu_type: "b200"
gpus_per_node: 8

frontend:
type: "dynamo"
args:
enforce-disagg: true
dynamo:
install: false
version: null

backend:
prefill_environment:
TORCH_DISTRIBUTED_DEFAULT_TIMEOUT: "1800"
PYTHONUNBUFFERED: "1"
DYN_SKIP_SGLANG_LOG_FORMATTING: "1"
SGLANG_DISAGGREGATION_HEARTBEAT_MAX_FAILURE: "100000"
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: "100000"
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: "100000"
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: "True"
SGLANG_USE_MESSAGE_QUEUE_BROADCASTER: "0"
NCCL_CUMEM_ENABLE: "1"
DYN_REQUEST_PLANE: "nats"

decode_environment:
TORCH_DISTRIBUTED_DEFAULT_TIMEOUT: "1800"
PYTHONUNBUFFERED: "1"
DYN_SKIP_SGLANG_LOG_FORMATTING: "1"
SGLANG_DISAGGREGATION_HEARTBEAT_MAX_FAILURE: "100000"
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: "100000"
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: "100000"
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: "True"
SGLANG_USE_MESSAGE_QUEUE_BROADCASTER: "0"
NCCL_CUMEM_ENABLE: "1"
DYN_REQUEST_PLANE: "nats"

sglang_config:
prefill:
# Model configuration
served-model-name: "GLM-5-FP8"
trust-remote-code: true
quantization: "fp8"
kv-cache-dtype: "fp8_e4m3"

# Disaggregation mode
disaggregation-mode: "prefill"
disaggregation-transfer-backend: "nixl"

# Size limits
max-running-requests: 160
cuda-graph-max-bs: 160
mem-fraction-static: 0.7
context-length: 16896
chunked-prefill-size: 131072
max-prefill-tokens: 16384

# Parallelism
tensor-parallel-size: 8
data-parallel-size: 8
expert-parallel-size: 1
enable-dp-attention: true
enable-dp-lm-head: true
load-balance-method: "total_tokens"

# Backend
nsa-decode-backend: "trtllm"
nsa-prefill-backend: "trtllm"
moe-runner-backend: "flashinfer_trtllm"

# Other flags
enable-flashinfer-allreduce-fusion: true
weight-loader-prefetch-checkpoints: true
disable-radix-cache: true
stream-interval: 30
model-loader-extra-config: '{"enable_multithread_load": true}'

decode:
# Model configuration
served-model-name: "GLM-5-FP8"
trust-remote-code: true

quantization: "fp8"
kv-cache-dtype: "fp8_e4m3"

# Disaggregation mode
disaggregation-mode: "decode"
disaggregation-transfer-backend: "nixl"

# Memory and token limits
mem-fraction-static: 0.8
context-length: 16896

# Parallelism
tensor-parallel-size: 8
expert-parallel-size: 1

# Backend
nsa-decode-backend: "trtllm"
nsa-prefill-backend: "trtllm"
moe-runner-backend: "flashinfer_trtllm"

# Other flags
enable-flashinfer-allreduce-fusion: true
weight-loader-prefetch-checkpoints: true
disable-radix-cache: true
stream-interval: 30
model-loader-extra-config: '{"enable_multithread_load": true}'

health_check:
max_attempts: 360
interval_seconds: 10

benchmark:
type: "sa-bench"
req_rate: "inf"

#### 16k512 low-latency sweep ####

zip_override_16k512_lowlat:
resources:
prefill_nodes: 1
prefill_workers: 1
decode_nodes: [2, 3, 4, 5, 7, 8]
decode_workers: [2, 3, 4, 5, 7, 8]
backend:
sglang_config:
decode:
data-parallel-size: 1

max-running-requests: [40, 24, 16, 12, 4, 1]
cuda-graph-max-bs: [40, 24, 16, 12, 4, 1]

benchmark:
isl: 16384
osl: 512
concurrencies: ["128", "128", "96", "64", "32", "8"]
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