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Prevent partial loading on mixed GPU brands

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In mult-brand GPU setups, if we couldn't fully load the model we
would fall through the scheduler and mistakenly try to load across
a mix of brands.  This makes sure we find the set of GPU(s) that
best fit for the partial load.
This commit is contained in:
Daniel Hiltgen
2024-07-22 11:57:26 -07:00
parent 0be8baad2b
commit 345420998e
2 changed files with 66 additions and 4 deletions
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31
server/sched.go
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@@ -212,9 +212,12 @@ func (s *Scheduler) processPending(ctx context.Context) {
} else if loadedCount == 0 {
// No models loaded. Load the model but prefer the best fit.
slog.Debug("loading first model", "model", pending.model.ModelPath)
g := pickBestFitGPUs(pending, ggml, gpus, &numParallel)
g := pickBestFullFitByLibrary(pending, ggml, gpus, &numParallel)
if g != nil {
gpus = g
} else {
// Only allow partial loads when this is the first model
gpus = pickBestPartialFitByLibrary(pending, ggml, gpus, &numParallel)
}
s.loadFn(pending, ggml, gpus, numParallel)
break
@@ -231,7 +234,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
// Update free memory from currently loaded models
s.updateFreeSpace(availGpus)
fitGpus := pickBestFitGPUs(pending, ggml, availGpus, &numParallel)
fitGpus := pickBestFullFitByLibrary(pending, ggml, availGpus, &numParallel)
if fitGpus != nil {
slog.Debug("new model fits with existing models, loading")
s.loadFn(pending, ggml, fitGpus, numParallel)
@@ -668,11 +671,12 @@ func (a ByDuration) Less(i, j int) bool {
// func (a BySize) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
// func (a BySize) Less(i, j int) bool { return a[i].estimatedVRAM < a[j].estimatedVRAM }
// pickBestFitGPUs will try to find the optimal placement of the model in the available GPUs where the model fully fits
// pickBestFullFitByLibrary will try to find the optimal placement of the model in the available GPUs where the model fully fits
// The list of GPUs returned will always be the same brand (library)
// If the model can not be fit fully within the available GPU(s) nil is returned
// If numParallel is <= 0, this will attempt try to optimize parallism based on available VRAM, and adjust
// opts.NumCtx accordingly
func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel *int) gpu.GpuInfoList {
func pickBestFullFitByLibrary(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel *int) gpu.GpuInfoList {
var estimatedVRAM uint64
var numParallelToTry []int
@@ -723,6 +727,25 @@ func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numP
return nil
}
// If multiple Libraries are detected, pick the Library which loads the most layers for the model
func pickBestPartialFitByLibrary(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel *int) gpu.GpuInfoList {
*numParallel = 1
byLibrary := gpus.ByLibrary()
if len(byLibrary) <= 1 {
return gpus
}
var bestEstimate uint64
var bestFit int
for i, gl := range byLibrary {
_, estimatedVRAM := llm.PredictServerFit(gl, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts)
if estimatedVRAM > bestEstimate {
bestEstimate = estimatedVRAM
bestFit = i
}
}
return byLibrary[bestFit]
}
// findRunnerToUnload finds a runner to unload to make room for a new model
func (s *Scheduler) findRunnerToUnload() *runnerRef {
s.loadedMu.Lock()