pub enum PerfModel {
Polynomial,
Interpolated {
prefill_interp: Arc<dyn PrefillInterpolator>,
decode_interp: Arc<dyn DecodeInterpolator>,
},
}Expand description
Performance model for predicting prefill and decode timing
Variants§
Polynomial
Default polynomial-based model using hardcoded formulas
Interpolated
Interpolation-based model using profiler data Interpolators are built once and stored as trait objects
Implementations§
Source§impl PerfModel
impl PerfModel
Sourcepub fn from_npz(path: &Path) -> Result<Self>
pub fn from_npz(path: &Path) -> Result<Self>
Load performance model from NPZ file
Expected arrays in NPZ file:
- prefill_isl: 1D array of input sequence lengths
- prefill_ttft_ms: 1D array of time to first token in milliseconds
- decode_active_kv_tokens: 1D array of active KV token counts
- decode_context_length: 1D array of context lengths
- decode_itl: 2D array of inter-token latencies in milliseconds
Sourcepub fn predict_prefill_time(&self, new_tokens: usize) -> f64
pub fn predict_prefill_time(&self, new_tokens: usize) -> f64
Predict prefill time in milliseconds given the number of new tokens
Sourcepub fn predict_decode_time(
&self,
active_kv_tokens: usize,
context_length: usize,
) -> f64
pub fn predict_decode_time( &self, active_kv_tokens: usize, context_length: usize, ) -> f64
Predict decode time in milliseconds given active KV tokens and context length
For the Polynomial variant, this computes active percentage as active_kv_tokens / 16384. For the Interpolated variant, this performs 2D bilinear interpolation.
Trait Implementations§
Auto Trait Implementations§
impl Freeze for PerfModel
impl !RefUnwindSafe for PerfModel
impl Send for PerfModel
impl Sync for PerfModel
impl Unpin for PerfModel
impl UnsafeUnpin for PerfModel
impl !UnwindSafe for PerfModel
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