chore: update ablation and clean configs

This commit is contained in:
2026-04-15 14:48:59 +08:00
parent eaf574cd4e
commit 365ceac3be
15 changed files with 879 additions and 324 deletions

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@@ -58,11 +58,19 @@ Prints `summary.json` to stdout and writes the full output directory
target/release/kvcache-sim ablate \ target/release/kvcache-sim ablate \
--config configs/glm5-8xb200-hf.yaml \ --config configs/glm5-8xb200-hf.yaml \
--routers random,least_loaded,least_tokens,min_pd,prefix_affinity \ --routers random,least_loaded,least_tokens,min_pd,prefix_affinity \
--evict-policies lru \
--output-dir runs/glm5_ablation --output-dir runs/glm5_ablation
``` ```
Writes one subdirectory per router plus a combined Writes `ablation.json` with one row per `router x evict_policy`.
`ablation.json` with side-by-side summaries.
`ablate` currently supports only `lru` as a valid eviction policy. The
aggregated output keeps the online prefill-time metrics
(`ttft_mean/p50/p95/p99`) and omits `e2e`.
The previous replay-based `belady` approximation has been removed from
the CLI because it was not an exact full-hierarchy Belady algorithm and
could produce misleading comparisons against `lru`.
### 3. Compute theoretical hit-rate ceilings (oracle) ### 3. Compute theoretical hit-rate ceilings (oracle)
@@ -115,7 +123,8 @@ so the same config can be reused across sweeps:
| `--ttl-seconds <S>` | `cluster.meta_store.ttl_seconds` | | `--ttl-seconds <S>` | `cluster.meta_store.ttl_seconds` |
`oracle` additionally takes `--capacity-blocks <N>` / `--per-instance` `oracle` additionally takes `--capacity-blocks <N>` / `--per-instance`
and `--out <PATH>`. `ablate` additionally takes `--routers <csv>`. and `--out <PATH>`. `ablate` additionally takes `--routers <csv>` and
`--evict-policies <csv>` (currently only `lru`).
## Router modes ## Router modes
@@ -288,12 +297,8 @@ memory_time = layers * weight_bytes_per_layer / gpu_mem_bw
| Config | Model | Hardware | Instances | Trace | | Config | Model | Hardware | Instances | Trace |
|--------|-------|----------|-----------|-------| |--------|-------|----------|-----------|-------|
| `glm5-8xb200-hf.yaml` | GLM-5 via HF config.json | 8xB200 preset | 32 | GLM coder blk512 | | `glm5-8xb200-hf.yaml` | GLM-5 via HF config.json | 8xB200 preset | 32 | GLM coder blk512 |
| `glm5-8xb200-blk512.yaml` | GLM-5 inline | 8xB200 inline | 64 | GLM coder blk512 | | `glm5-nvfp4-8xb300.yaml` | GLM-5-NVFP4 via HF config.json | 8xB300 preset | 8 | GLM coder blk512 |
| `glm5-8xb200.yaml` | GLM-5 inline | 8xB200 inline | 8 | GLM coder blk512 |
| `qwen3-coder-480b-8xh20.yaml` | Qwen3-Coder via HF | 8xH20 preset | 32 | Qwen coder blk16 | | `qwen3-coder-480b-8xh20.yaml` | Qwen3-Coder via HF | 8xH20 preset | 32 | Qwen coder blk16 |
| `qwen2.5-coder-7b-h800.yaml` | Qwen2.5-7B inline | H800 inline | 16 | Qwen coder blk16 |
| `qwen2.5-coder-7b-preset.yaml` | Qwen2.5-7B inline | H800 preset | 16 | Qwen coder blk16 |
| `qwen2.5-coder-32b-h800.yaml` | Qwen2.5-32B inline | H800 inline | 16 | Qwen coder blk16 |
## Outputs ## Outputs

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@@ -1,68 +0,0 @@
# GLM-5 (zai-org/GLM-5) on 8 x B200 SXM (192GB each).
# Architecture from HuggingFace config.json — all roofline coefficients
# are derived automatically.
model:
name: glm-5
# Core architecture (from HF config.json)
num_layers: 78
hidden_size: 6144
num_attention_heads: 64
num_kv_heads: 64 # formalism; MLA overrides KV cache sizing
head_dim: 64
intermediate_size: 12288 # shared expert FFN width
dtype_bytes: 2 # BF16
block_size_tokens: 512 # matches bailian-traces blksz_512
# MoE: 256 routed + 1 shared, 8 active per token
moe:
num_experts: 256
num_active_experts: 8
num_shared_experts: 1
expert_intermediate_size: 2048 # moe_intermediate_size
# MLA (Multi-head Latent Attention): compressed KV cache
mla:
kv_lora_rank: 512
q_lora_rank: 2048
qk_nope_head_dim: 192
qk_rope_head_dim: 64
v_head_dim: 256
# DSA (DeepSeek Sparse Attention): sub-quadratic past dense_window
attention:
type: dsa
dense_window: 4096
sparse_stride: 8
first_dense_layers: 3
hardware:
# Aggregate of 8 x B200 in one tensor-parallel group.
gpu_flops: 1.80e16 # 8 * 2.25 PFLOPS BF16 dense
gpu_mem_bw: 6.40e13 # 8 * 8 TB/s HBM3e
# KV budget after FP8 weights + activations. GLM-5 FP8 ~744GB of 1536GB.
hbm_bytes: 500.0e9
dram_bytes: 1.5e12 # ~1.5 TB usable CPU DRAM / v6d per node
pcie_bw: 128.0e9 # PCIe Gen6 x16
pcie_latency_us: 4.0
rdma_bw: 50.0e9 # ConnectX-7 400 Gbps
rdma_latency_us: 6.0
max_batch_slots: 256
prefill_chunk_tokens: 4096
cluster:
num_instances: 64
meta_store:
ttl_seconds: 300.0
router:
mode: min_pd
precise_probe_latency_us: 50.0
precise_probe_topk: 4
load_alpha: 1.0
sim:
trace_path: bailian-traces/glm_coder_blksz_512_040915-040917.jsonl
max_requests: null
output_dir: runs/glm5_8xb200_blk512
sample_interval_s: 1.0
seed: 42

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@@ -1,40 +0,0 @@
# GLM-5 using HuggingFace config.json + hardware preset.
#
# This config demonstrates the simplified format:
# model.config_json — loads architecture from HF config.json
# hardware.type — loads GPU specs from built-in preset
#
# Only deployment-specific fields need to be set explicitly.
# Any field from config_json or the preset can be overridden in YAML.
model:
# Auto-detect architecture: MoE, MLA, DSA, head dims, etc.
config_json: ../models/GLM-5/config.json
name: glm-5 # override HF model_type
dtype_bytes: 1 # BF16 (not in HF config.json)
block_size_tokens: 512 # matches bailian-traces blksz_512
hardware:
type: 8xb200 # 8 x B200 SXM (192GB each)
# Override preset values for this specific deployment:
hbm_bytes: 500.0e9 # KV budget after FP8 weights + activations
dram_bytes: 1.5e12 # ~1.5 TB usable CPU DRAM per node
max_batch_slots: 256
cluster:
num_instances: 32
meta_store:
ttl_seconds: 300.0
router:
mode: min_pd
precise_probe_latency_us: 50.0
precise_probe_topk: 4
load_alpha: 1.0
prefix_k: 8
sim:
trace_path: bailian-traces/glm_coder_blksz_512_040915-040917.jsonl
max_requests: null
output_dir: runs/glm5_8xb200_hf
sample_interval_s: 1.0
seed: 42

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@@ -1,66 +1,39 @@
# GLM-5 (zai-org/GLM-5) served as a single tensor-parallel instance on # GLM-5 using HuggingFace config.json + hardware preset.
# 8 x NVIDIA B200 SXM (192GB each, 1.5 TB aggregate HBM).
# #
# GLM-5 is a 744B-total / 40B-active Mixture-of-Experts model (BF16), # This config demonstrates the simplified format:
# using DeepSeek Sparse Attention (DSA). The HF card does not publish # model.config_json — loads architecture from HF config.json
# layer/head shapes, so the values below are reasonable estimates based # hardware.type — loads GPU specs from built-in preset
# on the GLM-4.5 lineage; adjust once the official config.json is public.
# #
# Hardware values below represent the *aggregate* of the 8-GPU TP group # Only deployment-specific fields need to be set explicitly.
# (one simulated "instance" == one 8xB200 serving replica). This is how # Any field from config_json or the preset can be overridden in YAML.
# the roofline in src/instance/compute.rs wants to see it: gpu_flops and
# gpu_mem_bw are the effective peaks seen by the TP'd model.
#
# Calibrate `flops_per_token_prefill` and `attn_quadratic_coeff` against
# measured prefill latency before trusting absolute TTFT numbers.
model: model:
name: glm-5 # Auto-detect architecture: MoE, MLA, DSA, head dims, etc.
# --- estimates; refine from official config.json when available --- config_json: ../models/GLM-5/config.json
num_layers: 92 name: glm-5 # override HF model_type
num_kv_heads: 8 # GQA dtype_bytes: 1 # BF16 (not in HF config.json)
head_dim: 128 block_size_tokens: 512 # matches bailian-traces blksz_512
dtype_bytes: 2 # BF16
block_size_tokens: 16 # trace convention
# Active-params-driven roofline: MoE activates ~40B params per token,
# so non-attention prefill FLOPs/token ≈ 2 * 40e9 = 8e10.
flops_per_token_prefill: 8.0e10
# Quadratic attention term ≈ 2 * num_heads * head_dim. GLM-5 uses
# DeepSeek Sparse Attention which is sub-quadratic in practice, so
# this coefficient is an upper bound — lower it if your measurements
# show DSA kicking in for long prompts.
attn_quadratic_coeff: 2048.0
bytes_per_token_prefill: 0.0
hardware: hardware:
# Aggregate of 8 x B200 in one tensor-parallel group. type: 8xb200 # 8 x B200 SXM (192GB each)
gpu_flops: 1.80e16 # 8 * 2.25 PFLOPS BF16 dense # Override preset values for this specific deployment:
gpu_mem_bw: 6.40e13 # 8 * 8 TB/s HBM3e hbm_bytes: 500.0e9 # KV budget after FP8 weights + activations
# KV-cache budget after weights + activations. GLM-5 @ BF16 is ~1.49TB, dram_bytes: 1.5e12 # ~1.5 TB usable CPU DRAM per node
# which barely fits in 1.5TB HBM; realistic serving uses FP8 weights
# (~744GB), leaving ~500GB for activations + KV cache. Adjust if your
# deployment uses a different weight dtype.
hbm_bytes: 500.0e9
dram_bytes: 1.5e12 # ~1.5 TB usable CPU DRAM / v6d per node
pcie_bw: 128.0e9 # PCIe Gen6 x16 ~ 128 GB/s per direction
pcie_latency_us: 4.0
rdma_bw: 50.0e9 # ConnectX-7 400 Gbps ≈ 50 GB/s
rdma_latency_us: 6.0
max_batch_slots: 256 max_batch_slots: 256
prefill_chunk_tokens: 2048
cluster: cluster:
num_instances: 8 # 8 TP replicas -> 64 B200s cluster-wide num_instances: 32
meta_store: meta_store:
ttl_seconds: 120.0 ttl_seconds: 300.0
router: router:
mode: ttl_aware mode: min_pd
precise_probe_latency_us: 50.0 precise_probe_latency_us: 50.0
precise_probe_topk: 4 precise_probe_topk: 4
load_alpha: 1.0 load_alpha: 1.0
prefix_k: 8
sim: sim:
trace_path: qwen-bailian-usagetraces-anon/qwen_coder_blksz_16.jsonl trace_path: bailian-traces/glm_coder_blksz_512_040915-040917.jsonl
max_requests: null max_requests: null
output_dir: runs/glm5_8xb200 output_dir: runs/glm5_8xb200
sample_interval_s: 1.0 sample_interval_s: 1.0

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@@ -1,42 +0,0 @@
# Qwen2.5-Coder-32B (dense, GQA) on H800 SXM (80GB).
# Architecture from HuggingFace config.json — roofline auto-derived.
model:
name: qwen2.5-coder-32b
num_layers: 64
hidden_size: 5120
num_attention_heads: 40
num_kv_heads: 8 # GQA
head_dim: 128
intermediate_size: 27648 # SwiGLU FFN
dtype_bytes: 2 # BF16
block_size_tokens: 16
hardware:
gpu_flops: 9.89e14
gpu_mem_bw: 3.35e12
hbm_bytes: 20.0e9 # smaller budget: 32B weights are large
dram_bytes: 512.0e9
pcie_bw: 64.0e9
pcie_latency_us: 5.0
rdma_bw: 25.0e9
rdma_latency_us: 8.0
max_batch_slots: 128
prefill_chunk_tokens: 1024
cluster:
num_instances: 16
meta_store:
ttl_seconds: 60.0
router:
mode: ttl_aware
precise_probe_latency_us: 50.0
precise_probe_topk: 4
load_alpha: 1.0
sim:
trace_path: traces/qwen_coder_blksz_16.jsonl
max_requests: null
output_dir: runs/qwen32b
sample_interval_s: 1.0
seed: 42

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@@ -1,42 +0,0 @@
# Qwen2.5-Coder-7B (dense, GQA) on a single H800 SXM (80GB).
# Architecture from HuggingFace config.json — roofline auto-derived.
model:
name: qwen2.5-coder-7b
num_layers: 28
hidden_size: 3584
num_attention_heads: 28
num_kv_heads: 4 # GQA: 28 query heads, 4 KV heads
head_dim: 128
intermediate_size: 18944 # SwiGLU FFN
dtype_bytes: 2 # BF16
block_size_tokens: 16 # matches qwen_coder_blksz_16 trace
hardware:
gpu_flops: 9.89e14 # H800 bf16 dense
gpu_mem_bw: 3.35e12 # 3.35 TB/s HBM3
hbm_bytes: 60.0e9 # leave headroom for weights/activations
dram_bytes: 512.0e9
pcie_bw: 64.0e9 # PCIe Gen5 x16
pcie_latency_us: 5.0
rdma_bw: 25.0e9 # ~200 Gbps NIC
rdma_latency_us: 8.0
max_batch_slots: 256
prefill_chunk_tokens: 2048
cluster:
num_instances: 16
meta_store:
ttl_seconds: 60.0
router:
mode: ttl_aware
precise_probe_latency_us: 50.0
precise_probe_topk: 4
load_alpha: 1.0
sim:
trace_path: qwen-bailian-usagetraces-anon/qwen_coder_blksz_16.jsonl
max_requests: null
output_dir: runs/qwen7b
sample_interval_s: 1.0
seed: 42

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@@ -1,36 +0,0 @@
# Qwen2.5-Coder-7B using hardware preset.
#
# Model architecture is specified inline (no config.json needed for simple
# models). Hardware uses preset "h800" with a single override for hbm_bytes.
model:
name: qwen2.5-coder-7b
num_layers: 28
hidden_size: 3584
num_attention_heads: 28
num_kv_heads: 4
head_dim: 128
intermediate_size: 18944
dtype_bytes: 2
block_size_tokens: 16
hardware:
type: h800 # single H800 SXM (80GB)
hbm_bytes: 60.0e9 # KV budget after 7B model weights
cluster:
num_instances: 16
meta_store:
ttl_seconds: 60.0
router:
mode: ttl_aware
precise_probe_latency_us: 50.0
precise_probe_topk: 4
load_alpha: 1.0
sim:
trace_path: qwen-bailian-usagetraces-anon/qwen_coder_blksz_16.jsonl
max_requests: null
output_dir: runs/qwen7b_preset
sample_interval_s: 1.0
seed: 42

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@@ -5,16 +5,17 @@ model:
config_json: ../models/Qwen3-Coder-480B-A35B-Instruct-FP8/config.json config_json: ../models/Qwen3-Coder-480B-A35B-Instruct-FP8/config.json
name: qwen3-coder-480b name: qwen3-coder-480b
dtype_bytes: 1 # FP8 inference dtype_bytes: 1 # FP8 inference
block_size_tokens: 16 block_size_tokens: 512
hardware: hardware:
type: 8xh20 type: 8xh20
hbm_bytes: 400.0e9 # KV budget after FP8 weights on 8x96GB hbm_bytes: 400.0e9 # KV budget after FP8 weights on 8x96GB
dram_bytes: 1.0e12 # ~1.0 TB usable CPU DRAM per node
cluster: cluster:
num_instances: 32 num_instances: 128
meta_store: meta_store:
ttl_seconds: 120.0 ttl_seconds: 300.0
router: router:
mode: min_pd mode: min_pd
precise_probe_latency_us: 50.0 precise_probe_latency_us: 50.0
@@ -22,7 +23,7 @@ cluster:
load_alpha: 1.0 load_alpha: 1.0
sim: sim:
trace_path: traces/qwen_coder_blksz_16.jsonl trace_path: bailian-traces/qwen3_coder_blksz_512_040915-040917.jsonl
max_requests: null max_requests: null
output_dir: runs/qwen3_coder_8xh20 output_dir: runs/qwen3_coder_8xh20
sample_interval_s: 1.0 sample_interval_s: 1.0

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@@ -6,11 +6,13 @@ use std::collections::HashMap;
use std::path::Path; use std::path::Path;
use crate::cluster::Cluster; use crate::cluster::Cluster;
use crate::config::Config; use crate::config::{Config, RouterMode};
use crate::metrics::ablation::AblationRow;
use crate::metrics::per_request::{PerRequestRow, PerRequestWriter}; use crate::metrics::per_request::{PerRequestRow, PerRequestWriter};
use crate::metrics::routing_log::RoutingLogWriter; use crate::metrics::routing_log::RoutingLogWriter;
use crate::metrics::summary::Summary; use crate::metrics::summary::Summary;
use crate::metrics::timeseries::{TimeseriesRow, TimeseriesWriter}; use crate::metrics::timeseries::{TimeseriesRow, TimeseriesWriter};
use crate::replay::ReplayEvictPolicy;
use crate::sim::{Event, EventQueue}; use crate::sim::{Event, EventQueue};
use crate::trace::{RequestRecord, TraceReader}; use crate::trace::{RequestRecord, TraceReader};
@@ -100,7 +102,12 @@ pub fn run(config: &Config, output_subdir: Option<&str>) -> Result<RunOutputs> {
if !inst.tick_scheduled { if !inst.tick_scheduled {
inst.tick_scheduled = true; inst.tick_scheduled = true;
let when = stats.ready_at.max(now); let when = stats.ready_at.max(now);
q.schedule(when, Event::BatchTick { instance: stats.instance }); q.schedule(
when,
Event::BatchTick {
instance: stats.instance,
},
);
} }
} }
Event::BatchTick { instance } => { Event::BatchTick { instance } => {
@@ -168,3 +175,33 @@ pub fn run(config: &Config, output_subdir: Option<&str>) -> Result<RunOutputs> {
Ok(RunOutputs { summary, rows }) Ok(RunOutputs { summary, rows })
} }
pub fn ablate_fixed_placement(
base: &Config,
routers: &[RouterMode],
evict_policies: &[ReplayEvictPolicy],
) -> Result<Vec<AblationRow>> {
let mut out = Vec::new();
for &policy in evict_policies {
if policy != ReplayEvictPolicy::Lru {
return Err(anyhow::anyhow!(
"exact belady is not supported for fixed-placement full-hierarchy ablation; \
the previous replay-based approximation has been removed"
));
}
}
for &mode in routers {
let mut cfg = base.clone();
cfg.cluster.router.mode = mode;
let placement_run = run(&cfg, Some(&format!("{}__placement_lru", mode.as_str())))?;
for &policy in evict_policies {
out.push(AblationRow::from_summary(
mode.as_str(),
policy,
"realized_lru",
&placement_run.summary,
));
}
}
Ok(out)
}

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@@ -7,6 +7,7 @@ pub mod instance;
pub mod metrics; pub mod metrics;
pub mod network; pub mod network;
pub mod oracle; pub mod oracle;
pub mod replay;
pub mod router; pub mod router;
pub mod sim; pub mod sim;
pub mod trace; pub mod trace;

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@@ -3,6 +3,7 @@ use clap::{Args, Parser, Subcommand};
use std::path::PathBuf; use std::path::PathBuf;
use kvcache_simulator::config::{Config, RouterMode}; use kvcache_simulator::config::{Config, RouterMode};
use kvcache_simulator::replay::ReplayEvictPolicy;
use kvcache_simulator::{driver, oracle, trace::TraceReader}; use kvcache_simulator::{driver, oracle, trace::TraceReader};
#[derive(Debug, Parser)] #[derive(Debug, Parser)]
@@ -74,7 +75,8 @@ enum Cmd {
#[command(flatten)] #[command(flatten)]
overrides: ConfigOverrides, overrides: ConfigOverrides,
}, },
/// Run the same trace under multiple routers and compare summaries. /// Run the same trace under multiple routers and fixed-placement eviction
/// policies, then compare cache-hit summaries.
Ablate { Ablate {
#[arg(short, long)] #[arg(short, long)]
config: PathBuf, config: PathBuf,
@@ -85,6 +87,10 @@ enum Cmd {
default_value = "random,least_loaded,least_tokens,ttl_aware,min_pd,cache_load,cache_score,estimated_ttft,prefix_affinity" default_value = "random,least_loaded,least_tokens,ttl_aware,min_pd,cache_load,cache_score,estimated_ttft,prefix_affinity"
)] )]
routers: String, routers: String,
/// Comma-separated eviction policies for ablation aggregation.
/// Currently only `lru` is supported.
#[arg(long, default_value = "lru")]
evict_policies: String,
#[command(flatten)] #[command(flatten)]
overrides: ConfigOverrides, overrides: ConfigOverrides,
}, },
@@ -125,8 +131,9 @@ fn main() -> Result<()> {
Cmd::Ablate { Cmd::Ablate {
config, config,
routers, routers,
evict_policies,
overrides, overrides,
} => cmd_ablate(&config, &routers, &overrides), } => cmd_ablate(&config, &routers, &evict_policies, &overrides),
Cmd::Validate { config, overrides } => cmd_validate(&config, &overrides), Cmd::Validate { config, overrides } => cmd_validate(&config, &overrides),
Cmd::Oracle { Cmd::Oracle {
config, config,
@@ -134,7 +141,13 @@ fn main() -> Result<()> {
capacity_blocks, capacity_blocks,
per_instance, per_instance,
out, out,
} => cmd_oracle(&config, &overrides, capacity_blocks, per_instance, out.as_deref()), } => cmd_oracle(
&config,
&overrides,
capacity_blocks,
per_instance,
out.as_deref(),
),
} }
} }
@@ -151,7 +164,12 @@ fn cmd_run(path: &PathBuf, overrides: &ConfigOverrides) -> Result<()> {
Ok(()) Ok(())
} }
fn cmd_ablate(path: &PathBuf, routers: &str, overrides: &ConfigOverrides) -> Result<()> { fn cmd_ablate(
path: &PathBuf,
routers: &str,
evict_policies: &str,
overrides: &ConfigOverrides,
) -> Result<()> {
let base = load(path, overrides)?; let base = load(path, overrides)?;
let modes: Vec<RouterMode> = routers let modes: Vec<RouterMode> = routers
.split(',') .split(',')
@@ -160,15 +178,27 @@ fn cmd_ablate(path: &PathBuf, routers: &str, overrides: &ConfigOverrides) -> Res
.map(RouterMode::parse) .map(RouterMode::parse)
.collect::<Result<Vec<_>>>() .collect::<Result<Vec<_>>>()
.with_context(|| format!("parsing --routers='{routers}'"))?; .with_context(|| format!("parsing --routers='{routers}'"))?;
let mut all = Vec::new(); let policies: Vec<ReplayEvictPolicy> = evict_policies
for mode in modes { .split(',')
let mut cfg = base.clone(); .map(|s| s.trim())
cfg.cluster.router.mode = mode; .filter(|s| !s.is_empty())
let sub = mode.as_str().to_string(); .map(ReplayEvictPolicy::parse)
eprintln!("[ablate] running router={}", sub); .collect::<Result<Vec<_>>>()
let out = driver::run(&cfg, Some(&sub))?; .with_context(|| format!("parsing --evict-policies='{evict_policies}'"))?;
all.push(out.summary); eprintln!(
} "[ablate] routers={} evict_policies={}",
modes
.iter()
.map(RouterMode::as_str)
.collect::<Vec<_>>()
.join(","),
policies
.iter()
.map(ReplayEvictPolicy::as_str)
.collect::<Vec<_>>()
.join(",")
);
let all = driver::ablate_fixed_placement(&base, &modes, &policies)?;
let agg_path = std::path::Path::new(&base.sim.output_dir).join("ablation.json"); let agg_path = std::path::Path::new(&base.sim.output_dir).join("ablation.json");
std::fs::create_dir_all(&base.sim.output_dir)?; std::fs::create_dir_all(&base.sim.output_dir)?;
std::fs::write(&agg_path, serde_json::to_string_pretty(&all)?)?; std::fs::write(&agg_path, serde_json::to_string_pretty(&all)?)?;
@@ -181,13 +211,25 @@ fn cmd_validate(path: &PathBuf, overrides: &ConfigOverrides) -> Result<()> {
use kvcache_simulator::instance::compute::ComputeModel; use kvcache_simulator::instance::compute::ComputeModel;
let cfg = load(path, overrides)?; let cfg = load(path, overrides)?;
eprintln!("config OK: {}", cfg.model.name); eprintln!("config OK: {}", cfg.model.name);
eprintln!("mode = {}", if cfg.model.is_arch_mode() { "architecture-derived" } else { "legacy manual" }); eprintln!(
"mode = {}",
if cfg.model.is_arch_mode() {
"architecture-derived"
} else {
"legacy manual"
}
);
let cm = ComputeModel::new(&cfg.model, &cfg.hardware); let cm = ComputeModel::new(&cfg.model, &cfg.hardware);
eprintln!("compute: {}", cm.describe()); eprintln!("compute: {}", cm.describe());
eprintln!("kv_block_bytes = {} ({:.2} MB{})", eprintln!(
"kv_block_bytes = {} ({:.2} MB{})",
cfg.model.kv_block_bytes(), cfg.model.kv_block_bytes(),
cfg.model.kv_block_bytes() as f64 / 1e6, cfg.model.kv_block_bytes() as f64 / 1e6,
if cfg.model.mla.is_some() { ", MLA compressed" } else { "" }, if cfg.model.mla.is_some() {
", MLA compressed"
} else {
""
},
); );
let block_bytes = cfg.model.kv_block_bytes() as f64; let block_bytes = cfg.model.kv_block_bytes() as f64;
let hbm_blocks = (cfg.hardware.hbm_bytes / block_bytes) as u64; let hbm_blocks = (cfg.hardware.hbm_bytes / block_bytes) as u64;
@@ -251,7 +293,11 @@ fn cmd_oracle(
capacity, capacity,
per_instance_blocks, per_instance_blocks,
cfg.cluster.num_instances, cfg.cluster.num_instances,
if per_instance { ", per-instance mode" } else { "" } if per_instance {
", per-instance mode"
} else {
""
}
); );
let result = oracle::analyze(&records, capacity); let result = oracle::analyze(&records, capacity);

50
src/metrics/ablation.rs Normal file
View File

@@ -0,0 +1,50 @@
use serde::Serialize;
use crate::metrics::Summary;
use crate::replay::ReplayEvictPolicy;
#[derive(Debug, Clone, Serialize)]
pub struct AblationRow {
pub router: String,
pub evict_policy: String,
pub placement_source: String,
pub num_requests: u64,
pub total_blocks: u64,
pub ttft_mean: f64,
pub ttft_p50: f64,
pub ttft_p95: f64,
pub ttft_p99: f64,
pub hit_rate_l0: f64,
pub hit_rate_l1: f64,
pub hit_rate_remote: f64,
pub miss_rate: f64,
pub total_rdma_bytes: u64,
pub total_pcie_bytes: u64,
}
impl AblationRow {
pub fn from_summary(
router: &str,
policy: ReplayEvictPolicy,
placement_source: &str,
summary: &Summary,
) -> Self {
Self {
router: router.to_string(),
evict_policy: policy.as_str().to_string(),
placement_source: placement_source.to_string(),
num_requests: summary.num_requests,
total_blocks: summary.total_blocks,
ttft_mean: summary.ttft_mean,
ttft_p50: summary.ttft_p50,
ttft_p95: summary.ttft_p95,
ttft_p99: summary.ttft_p99,
hit_rate_l0: summary.hit_rate_l0,
hit_rate_l1: summary.hit_rate_l1,
hit_rate_remote: summary.hit_rate_remote,
miss_rate: summary.miss_rate,
total_rdma_bytes: summary.total_rdma_bytes,
total_pcie_bytes: summary.total_pcie_bytes,
}
}
}

View File

@@ -1,7 +1,9 @@
pub mod ablation;
pub mod per_request; pub mod per_request;
pub mod routing_log; pub mod routing_log;
pub mod summary; pub mod summary;
pub mod timeseries; pub mod timeseries;
pub use ablation::AblationRow;
pub use per_request::PerRequestRow; pub use per_request::PerRequestRow;
pub use summary::Summary; pub use summary::Summary;

608
src/replay.rs Normal file
View File

@@ -0,0 +1,608 @@
use ahash::{AHashMap, AHashSet};
use anyhow::{anyhow, Result};
use serde::Serialize;
use std::cmp::min;
use std::collections::BinaryHeap;
use crate::config::Config;
use crate::instance::kv_cache::LruBlocks;
use crate::trace::RequestRecord;
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize)]
#[serde(rename_all = "snake_case")]
pub enum ReplayEvictPolicy {
Lru,
Belady,
}
impl ReplayEvictPolicy {
pub fn parse(s: &str) -> Result<Self> {
match s {
"lru" => Ok(Self::Lru),
"belady" => Err(anyhow!(
"exact belady is not supported for fixed-placement full-hierarchy ablation"
)),
other => Err(anyhow!("unknown evict policy: {other}")),
}
}
pub fn as_str(&self) -> &'static str {
match self {
Self::Lru => "lru",
Self::Belady => "belady",
}
}
}
#[derive(Debug, Clone)]
pub struct PlacementEntry {
pub req_id: u64,
pub instance: u32,
}
#[derive(Debug, Clone, Serialize, Default)]
pub struct ReplaySummary {
pub num_requests: u64,
pub total_blocks: u64,
pub l0_hit_blocks: u64,
pub l1_hit_blocks: u64,
pub remote_hit_blocks: u64,
pub miss_blocks: u64,
pub hit_rate_l0: f64,
pub hit_rate_l1: f64,
pub hit_rate_remote: f64,
pub miss_rate: f64,
pub total_rdma_bytes: u64,
pub total_pcie_bytes: u64,
}
impl ReplaySummary {
fn from_counts(
num_requests: usize,
total_blocks: u64,
l0_hit_blocks: u64,
l1_hit_blocks: u64,
remote_hit_blocks: u64,
miss_blocks: u64,
total_rdma_bytes: u64,
total_pcie_bytes: u64,
) -> Self {
let denom = total_blocks.max(1) as f64;
Self {
num_requests: num_requests as u64,
total_blocks,
l0_hit_blocks,
l1_hit_blocks,
remote_hit_blocks,
miss_blocks,
hit_rate_l0: l0_hit_blocks as f64 / denom,
hit_rate_l1: l1_hit_blocks as f64 / denom,
hit_rate_remote: remote_hit_blocks as f64 / denom,
miss_rate: miss_blocks as f64 / denom,
total_rdma_bytes,
total_pcie_bytes,
}
}
}
#[derive(Debug, Clone, Copy)]
enum FutureKind {
L0,
L1,
}
#[derive(Debug)]
struct FutureIndex {
local: AHashMap<(u32, u64), Vec<usize>>,
global: AHashMap<u64, Vec<(usize, u32)>>,
}
impl FutureIndex {
fn build(records: &[RequestRecord], placement: &[u32]) -> Self {
let mut local: AHashMap<(u32, u64), Vec<usize>> = AHashMap::new();
let mut global: AHashMap<u64, Vec<(usize, u32)>> = AHashMap::new();
for (req_idx, record) in records.iter().enumerate() {
let inst = placement[req_idx];
let mut seen = AHashSet::new();
for &block in &record.hash_ids {
if !seen.insert(block) {
continue;
}
local.entry((inst, block)).or_default().push(req_idx);
global.entry(block).or_default().push((req_idx, inst));
}
}
Self { local, global }
}
fn next_local(&self, inst: u32, block: u64, current_req_idx: usize) -> usize {
match self.local.get(&(inst, block)) {
Some(indices) => next_after(indices, current_req_idx),
None => usize::MAX,
}
}
fn next_other(&self, inst: u32, block: u64, current_req_idx: usize) -> usize {
let Some(indices) = self.global.get(&block) else {
return usize::MAX;
};
let start = first_after_pair(indices, current_req_idx);
for &(req_idx, owner_inst) in indices.iter().skip(start) {
if owner_inst != inst {
return req_idx;
}
}
usize::MAX
}
fn next_use(&self, kind: FutureKind, inst: u32, block: u64, current_req_idx: usize) -> usize {
match kind {
FutureKind::L0 => self.next_local(inst, block, current_req_idx),
FutureKind::L1 => min(
self.next_local(inst, block, current_req_idx),
self.next_other(inst, block, current_req_idx),
),
}
}
}
fn next_after(indices: &[usize], current_req_idx: usize) -> usize {
let pos = indices.partition_point(|&idx| idx <= current_req_idx);
indices.get(pos).copied().unwrap_or(usize::MAX)
}
fn first_after_pair(indices: &[(usize, u32)], current_req_idx: usize) -> usize {
indices.partition_point(|&(idx, _)| idx <= current_req_idx)
}
#[derive(Debug)]
struct BeladyTier {
capacity: usize,
resident: AHashSet<u64>,
versions: AHashMap<u64, u64>,
heap: BinaryHeap<(usize, u64, u64)>,
next_version: u64,
}
impl BeladyTier {
fn new(capacity: usize) -> Self {
Self {
capacity,
resident: AHashSet::with_capacity(capacity),
versions: AHashMap::with_capacity(capacity),
heap: BinaryHeap::with_capacity(capacity),
next_version: 0,
}
}
fn contains(&self, key: u64) -> bool {
self.resident.contains(&key)
}
fn remove(&mut self, key: u64) -> bool {
if self.resident.remove(&key) {
self.versions.remove(&key);
true
} else {
false
}
}
fn touch(
&mut self,
key: u64,
current_req_idx: usize,
kind: FutureKind,
inst: u32,
futures: &FutureIndex,
) -> bool {
if !self.resident.contains(&key) {
return false;
}
self.next_version += 1;
let version = self.next_version;
let next_use = futures.next_use(kind, inst, key, current_req_idx);
self.versions.insert(key, version);
self.heap.push((next_use, version, key));
true
}
fn insert(
&mut self,
key: u64,
current_req_idx: usize,
kind: FutureKind,
inst: u32,
futures: &FutureIndex,
) -> Option<u64> {
if self.touch(key, current_req_idx, kind, inst, futures) {
return None;
}
if self.capacity == 0 {
return Some(key);
}
let mut evicted = None;
if self.resident.len() == self.capacity {
evicted = self.evict(current_req_idx, kind, inst, futures);
}
self.next_version += 1;
let version = self.next_version;
let next_use = futures.next_use(kind, inst, key, current_req_idx);
self.resident.insert(key);
self.versions.insert(key, version);
self.heap.push((next_use, version, key));
evicted
}
fn evict(
&mut self,
current_req_idx: usize,
kind: FutureKind,
inst: u32,
futures: &FutureIndex,
) -> Option<u64> {
while let Some((stored_next_use, version, key)) = self.heap.pop() {
if !self.resident.contains(&key) {
continue;
}
let Some(current_version) = self.versions.get(&key).copied() else {
continue;
};
if current_version != version {
continue;
}
let actual_next_use = futures.next_use(kind, inst, key, current_req_idx);
if actual_next_use != stored_next_use {
self.next_version += 1;
let new_version = self.next_version;
self.versions.insert(key, new_version);
self.heap.push((actual_next_use, new_version, key));
continue;
}
self.resident.remove(&key);
self.versions.remove(&key);
return Some(key);
}
None
}
}
#[derive(Debug)]
enum Tier {
Lru(LruBlocks),
Belady(BeladyTier),
}
impl Tier {
fn new(policy: ReplayEvictPolicy, capacity: usize) -> Self {
match policy {
ReplayEvictPolicy::Lru => Self::Lru(LruBlocks::new(capacity)),
ReplayEvictPolicy::Belady => Self::Belady(BeladyTier::new(capacity)),
}
}
fn contains(&self, key: u64) -> bool {
match self {
Self::Lru(tier) => tier.contains(key),
Self::Belady(tier) => tier.contains(key),
}
}
fn remove(&mut self, key: u64) -> bool {
match self {
Self::Lru(tier) => tier.remove(key),
Self::Belady(tier) => tier.remove(key),
}
}
fn touch(
&mut self,
key: u64,
req_idx: usize,
kind: FutureKind,
inst: u32,
futures: &FutureIndex,
) -> bool {
match self {
Self::Lru(tier) => tier.touch(key),
Self::Belady(tier) => tier.touch(key, req_idx, kind, inst, futures),
}
}
fn insert(
&mut self,
key: u64,
req_idx: usize,
kind: FutureKind,
inst: u32,
futures: &FutureIndex,
) -> Option<u64> {
match self {
Self::Lru(tier) => tier.insert_block(key),
Self::Belady(tier) => tier.insert(key, req_idx, kind, inst, futures),
}
}
fn longest_prefix_touch(
&mut self,
hashes: &[u64],
req_idx: usize,
kind: FutureKind,
inst: u32,
futures: &FutureIndex,
) -> usize {
match self {
Self::Lru(tier) => tier.longest_prefix(hashes),
Self::Belady(tier) => {
let mut matched = 0usize;
for &hash in hashes {
if !tier.touch(hash, req_idx, kind, inst, futures) {
break;
}
matched += 1;
}
matched
}
}
}
fn longest_prefix_peek(&self, hashes: &[u64]) -> usize {
match self {
Self::Lru(tier) => tier.longest_prefix_peek(hashes),
Self::Belady(tier) => {
let mut matched = 0usize;
for &hash in hashes {
if !tier.contains(hash) {
break;
}
matched += 1;
}
matched
}
}
}
}
#[derive(Debug)]
struct ReplayInstanceCache {
l0: Tier,
l1: Tier,
}
impl ReplayInstanceCache {
fn new(policy: ReplayEvictPolicy, l0_cap: usize, l1_cap: usize) -> Self {
Self {
l0: Tier::new(policy, l0_cap),
l1: Tier::new(policy, l1_cap),
}
}
fn promote_l1_blocks_to_l0(
&mut self,
hashes: &[u64],
req_idx: usize,
inst: u32,
futures: &FutureIndex,
owners: &mut AHashMap<u64, AHashSet<u32>>,
) {
for &hash in hashes {
if self.l1.remove(hash) {
remove_owner(owners, hash, inst);
}
self.insert_block_into_l0(hash, req_idx, inst, futures, owners);
}
}
fn fetch_remote_blocks_to_l0(
&mut self,
hashes: &[u64],
req_idx: usize,
inst: u32,
futures: &FutureIndex,
owners: &mut AHashMap<u64, AHashSet<u32>>,
) {
for &hash in hashes {
self.stage_remote_block_in_l1(hash, req_idx, inst, futures, owners);
if self.l1.remove(hash) {
remove_owner(owners, hash, inst);
}
self.insert_block_into_l0(hash, req_idx, inst, futures, owners);
}
}
fn insert_blocks_into_l0(
&mut self,
hashes: &[u64],
req_idx: usize,
inst: u32,
futures: &FutureIndex,
owners: &mut AHashMap<u64, AHashSet<u32>>,
) {
for &hash in hashes {
self.insert_block_into_l0(hash, req_idx, inst, futures, owners);
}
}
fn insert_block_into_l0(
&mut self,
hash: u64,
req_idx: usize,
inst: u32,
futures: &FutureIndex,
owners: &mut AHashMap<u64, AHashSet<u32>>,
) {
if self.l0.touch(hash, req_idx, FutureKind::L0, inst, futures) {
return;
}
if self.l1.remove(hash) {
remove_owner(owners, hash, inst);
}
if let Some(evicted_l0) = self.l0.insert(hash, req_idx, FutureKind::L0, inst, futures) {
self.demote_into_l1(evicted_l0, req_idx, inst, futures, owners);
}
}
fn stage_remote_block_in_l1(
&mut self,
hash: u64,
req_idx: usize,
inst: u32,
futures: &FutureIndex,
owners: &mut AHashMap<u64, AHashSet<u32>>,
) {
if self.l0.contains(hash) || self.l1.contains(hash) {
return;
}
if let Some(evicted_l1) = self.l1.insert(hash, req_idx, FutureKind::L1, inst, futures) {
remove_owner(owners, evicted_l1, inst);
}
add_owner(owners, hash, inst);
}
fn demote_into_l1(
&mut self,
hash: u64,
req_idx: usize,
inst: u32,
futures: &FutureIndex,
owners: &mut AHashMap<u64, AHashSet<u32>>,
) {
if self.l1.touch(hash, req_idx, FutureKind::L1, inst, futures) {
return;
}
if let Some(evicted_l1) = self.l1.insert(hash, req_idx, FutureKind::L1, inst, futures) {
remove_owner(owners, evicted_l1, inst);
}
add_owner(owners, hash, inst);
}
}
fn add_owner(owners: &mut AHashMap<u64, AHashSet<u32>>, hash: u64, inst: u32) {
owners.entry(hash).or_default().insert(inst);
}
fn remove_owner(owners: &mut AHashMap<u64, AHashSet<u32>>, hash: u64, inst: u32) {
if let Some(bucket) = owners.get_mut(&hash) {
bucket.remove(&inst);
if bucket.is_empty() {
owners.remove(&hash);
}
}
}
pub fn replay_fixed_placement(
cfg: &Config,
records: &[RequestRecord],
placements: &[PlacementEntry],
policy: ReplayEvictPolicy,
) -> Result<ReplaySummary> {
if records.len() != placements.len() {
return Err(anyhow!(
"records/placements length mismatch: {} vs {}",
records.len(),
placements.len()
));
}
let placement_by_req: AHashMap<u64, u32> =
placements.iter().map(|p| (p.req_id, p.instance)).collect();
let ordered_placement: Vec<u32> = records
.iter()
.map(|r| {
placement_by_req
.get(&r.req_id)
.copied()
.ok_or_else(|| anyhow!("missing placement for req_id={}", r.req_id))
})
.collect::<Result<_>>()?;
let futures = FutureIndex::build(records, &ordered_placement);
let block_bytes = cfg.model.kv_block_bytes() as f64;
let l0_cap = (cfg.hardware.hbm_bytes / block_bytes).max(1.0) as usize;
let l1_cap = (cfg.hardware.dram_bytes / block_bytes).max(1.0) as usize;
let num_instances = cfg.cluster.num_instances as usize;
let mut caches: Vec<ReplayInstanceCache> = (0..num_instances)
.map(|_| ReplayInstanceCache::new(policy, l0_cap, l1_cap))
.collect();
let mut owners: AHashMap<u64, AHashSet<u32>> = AHashMap::new();
let mut total_blocks = 0u64;
let mut l0_hit_blocks = 0u64;
let mut l1_hit_blocks = 0u64;
let mut remote_hit_blocks = 0u64;
let mut miss_blocks = 0u64;
let mut total_rdma_bytes = 0u64;
let mut total_pcie_bytes = 0u64;
for (req_idx, record) in records.iter().enumerate() {
let inst = ordered_placement[req_idx];
let cache = &mut caches[inst as usize];
total_blocks += record.hash_ids.len() as u64;
let l0_hits = cache.l0.longest_prefix_touch(
&record.hash_ids,
req_idx,
FutureKind::L0,
inst,
&futures,
);
let suffix_after_l0 = &record.hash_ids[l0_hits..];
let l1_hits = cache.l1.longest_prefix_peek(suffix_after_l0);
if l1_hits > 0 {
cache.promote_l1_blocks_to_l0(
&suffix_after_l0[..l1_hits],
req_idx,
inst,
&futures,
&mut owners,
);
}
let suffix_after_l1 = &suffix_after_l0[l1_hits..];
let mut remote_hits = 0usize;
for &hash in suffix_after_l1 {
let any_remote = owners
.get(&hash)
.map(|bucket| bucket.iter().any(|owner| *owner != inst))
.unwrap_or(false);
if any_remote {
remote_hits += 1;
} else {
break;
}
}
if remote_hits > 0 {
cache.fetch_remote_blocks_to_l0(
&suffix_after_l1[..remote_hits],
req_idx,
inst,
&futures,
&mut owners,
);
}
let misses = record.hash_ids.len() - l0_hits - l1_hits - remote_hits;
let new_input = &record.hash_ids[(l0_hits + l1_hits + remote_hits)..];
if !new_input.is_empty() {
cache.insert_blocks_into_l0(new_input, req_idx, inst, &futures, &mut owners);
}
l0_hit_blocks += l0_hits as u64;
l1_hit_blocks += l1_hits as u64;
remote_hit_blocks += remote_hits as u64;
miss_blocks += misses as u64;
let kv_block_bytes = cfg.model.kv_block_bytes();
total_rdma_bytes += (remote_hits as u64) * kv_block_bytes;
total_pcie_bytes += ((l1_hits + remote_hits) as u64) * kv_block_bytes;
}
Ok(ReplaySummary::from_counts(
records.len(),
total_blocks,
l0_hit_blocks,
l1_hit_blocks,
remote_hit_blocks,
miss_blocks,
total_rdma_bytes,
total_pcie_bytes,
))
}

View File

@@ -6,6 +6,7 @@ use std::io::Write;
use kvcache_simulator::config::*; use kvcache_simulator::config::*;
use kvcache_simulator::driver; use kvcache_simulator::driver;
use kvcache_simulator::replay::ReplayEvictPolicy;
fn base_config(trace_path: &str, out_dir: &str, mode: RouterMode) -> Config { fn base_config(trace_path: &str, out_dir: &str, mode: RouterMode) -> Config {
Config { Config {
@@ -36,7 +37,9 @@ fn base_config(trace_path: &str, out_dir: &str, mode: RouterMode) -> Config {
}, },
cluster: ClusterConfig { cluster: ClusterConfig {
num_instances: 4, num_instances: 4,
meta_store: MetaStoreConfig { ttl_seconds: 1000.0 }, meta_store: MetaStoreConfig {
ttl_seconds: 1000.0,
},
router: RouterConfig { router: RouterConfig {
mode, mode,
precise_probe_latency_us: 10.0, precise_probe_latency_us: 10.0,
@@ -94,9 +97,11 @@ fn write_synthetic_trace(path: &std::path::Path) {
} }
} }
fn run(mode: RouterMode, trace_path: &std::path::Path, out_root: &std::path::Path) fn run(
-> kvcache_simulator::metrics::Summary mode: RouterMode,
{ trace_path: &std::path::Path,
out_root: &std::path::Path,
) -> kvcache_simulator::metrics::Summary {
let cfg = base_config( let cfg = base_config(
trace_path.to_str().unwrap(), trace_path.to_str().unwrap(),
out_root.to_str().unwrap(), out_root.to_str().unwrap(),
@@ -119,9 +124,8 @@ fn ablation_hit_rate_ordering() {
let s_ttl = run(RouterMode::TtlAware, &trace_path, &tmp); let s_ttl = run(RouterMode::TtlAware, &trace_path, &tmp);
let s_prec = run(RouterMode::Precise, &trace_path, &tmp); let s_prec = run(RouterMode::Precise, &trace_path, &tmp);
let total_hit = |s: &kvcache_simulator::metrics::Summary| { let total_hit =
s.hit_rate_l0 + s.hit_rate_l1 + s.hit_rate_remote |s: &kvcache_simulator::metrics::Summary| s.hit_rate_l0 + s.hit_rate_l1 + s.hit_rate_remote;
};
let h_rand = total_hit(&s_random); let h_rand = total_hit(&s_random);
let h_ll = total_hit(&s_ll); let h_ll = total_hit(&s_ll);
@@ -135,23 +139,79 @@ fn ablation_hit_rate_ordering() {
eprintln!( eprintln!(
" remote+local hit ratio L0/L1/remote: \ " remote+local hit ratio L0/L1/remote: \
random=({:.2},{:.2},{:.2}) precise=({:.2},{:.2},{:.2})", random=({:.2},{:.2},{:.2}) precise=({:.2},{:.2},{:.2})",
s_random.hit_rate_l0, s_random.hit_rate_l1, s_random.hit_rate_remote, s_random.hit_rate_l0,
s_prec.hit_rate_l0, s_prec.hit_rate_l1, s_prec.hit_rate_remote, s_random.hit_rate_l1,
s_random.hit_rate_remote,
s_prec.hit_rate_l0,
s_prec.hit_rate_l1,
s_prec.hit_rate_remote,
); );
// ttl_aware and precise should outperform random / least_loaded for // ttl_aware and precise should outperform random / least_loaded for
// a workload built entirely of shared-prefix conversations. // a workload built entirely of shared-prefix conversations.
let eps = 1e-6; let eps = 1e-6;
assert!( assert!(h_ttl + eps >= h_rand, "ttl_aware should >= random hit rate");
h_ttl + eps >= h_rand, assert!(h_prec + eps >= h_rand, "precise should >= random hit rate");
"ttl_aware should >= random hit rate"
);
assert!(
h_prec + eps >= h_rand,
"precise should >= random hit rate"
);
assert!( assert!(
h_prec + eps >= h_ll, h_prec + eps >= h_ll,
"precise should >= least_loaded hit rate" "precise should >= least_loaded hit rate"
); );
} }
#[test]
fn ablation_lru_preserves_ttft_fields() {
let tmp = std::env::temp_dir().join("kvcache_sim_replay");
let _ = std::fs::remove_dir_all(&tmp);
std::fs::create_dir_all(&tmp).unwrap();
let trace_path = tmp.join("trace.jsonl");
write_synthetic_trace(&trace_path);
let cfg = base_config(
trace_path.to_str().unwrap(),
tmp.to_str().unwrap(),
RouterMode::Random,
);
let online = driver::run(&cfg, Some("online_lru")).expect("online lru run");
let out = driver::ablate_fixed_placement(&cfg, &[RouterMode::Random], &[ReplayEvictPolicy::Lru])
.expect("ablate lru");
assert_eq!(out.len(), 1);
let row = &out[0];
let online_hit = online.summary.hit_rate_l0 + online.summary.hit_rate_l1 + online.summary.hit_rate_remote;
let ablate_hit = row.hit_rate_l0 + row.hit_rate_l1 + row.hit_rate_remote;
assert!(
(ablate_hit - online_hit).abs() < 1e-9,
"ablation lru should match online lru hit rate: online={online_hit} ablate={ablate_hit}"
);
assert!((row.ttft_mean - online.summary.ttft_mean).abs() < 1e-9);
assert!((row.ttft_p50 - online.summary.ttft_p50).abs() < 1e-9);
assert!((row.ttft_p95 - online.summary.ttft_p95).abs() < 1e-9);
assert!((row.ttft_p99 - online.summary.ttft_p99).abs() < 1e-9);
}
#[test]
fn ablate_rejects_belady_until_exact_algorithm_exists() {
let tmp = std::env::temp_dir().join("kvcache_sim_ablate_evict");
let _ = std::fs::remove_dir_all(&tmp);
std::fs::create_dir_all(&tmp).unwrap();
let trace_path = tmp.join("trace.jsonl");
write_synthetic_trace(&trace_path);
let cfg = base_config(
trace_path.to_str().unwrap(),
tmp.to_str().unwrap(),
RouterMode::Random,
);
let err = driver::ablate_fixed_placement(
&cfg,
&[RouterMode::Random],
&[ReplayEvictPolicy::Belady],
)
.expect_err("belady should be rejected");
assert!(
err.to_string().contains("exact belady"),
"unexpected error: {err:#}"
);
}