Prevent partial loading on mixed GPU brands

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

View file

@ -212,9 +212,12 @@ func (s *Scheduler) processPending(ctx context.Context) {
} else if loadedCount == 0 { } else if loadedCount == 0 {
// No models loaded. Load the model but prefer the best fit. // No models loaded. Load the model but prefer the best fit.
slog.Debug("loading first model", "model", pending.model.ModelPath) slog.Debug("loading first model", "model", pending.model.ModelPath)
g := pickBestFitGPUs(pending, ggml, gpus, &numParallel) g := pickBestFullFitByLibrary(pending, ggml, gpus, &numParallel)
if g != nil { if g != nil {
gpus = g 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) s.loadFn(pending, ggml, gpus, numParallel)
break break
@ -231,7 +234,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
// Update free memory from currently loaded models // Update free memory from currently loaded models
s.updateFreeSpace(availGpus) s.updateFreeSpace(availGpus)
fitGpus := pickBestFitGPUs(pending, ggml, availGpus, &numParallel) fitGpus := pickBestFullFitByLibrary(pending, ggml, availGpus, &numParallel)
if fitGpus != nil { if fitGpus != nil {
slog.Debug("new model fits with existing models, loading") slog.Debug("new model fits with existing models, loading")
s.loadFn(pending, ggml, fitGpus, numParallel) 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) 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 } // 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 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 // If numParallel is <= 0, this will attempt try to optimize parallism based on available VRAM, and adjust
// opts.NumCtx accordingly // 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 estimatedVRAM uint64
var numParallelToTry []int var numParallelToTry []int
@ -723,6 +727,25 @@ func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numP
return nil 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 // findRunnerToUnload finds a runner to unload to make room for a new model
func (s *Scheduler) findRunnerToUnload() *runnerRef { func (s *Scheduler) findRunnerToUnload() *runnerRef {
s.loadedMu.Lock() s.loadedMu.Lock()

View file

@ -666,6 +666,45 @@ func TestAlreadyCanceled(t *testing.T) {
require.Empty(t, scenario1a.req.successCh) require.Empty(t, scenario1a.req.successCh)
} }
func TestHomogeneousGPUs(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 100*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.getGpuFn = func() gpu.GpuInfoList {
// Set memory values to require the model to be spread
gpus := []gpu.GpuInfo{
{Library: "cuda"},
{Library: "rocm"},
}
gpus[0].TotalMemory = 1 * format.GibiByte
gpus[0].FreeMemory = 256 * format.MebiByte
gpus[1].TotalMemory = 1 * format.GibiByte
gpus[1].FreeMemory = 256 * format.MebiByte
return gpus
}
s.getCpuFn = getCpuFn
a := newScenarioRequest(t, ctx, "ollama-model-1", 10, &api.Duration{Duration: 5 * time.Millisecond})
s.newServerFn = func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
require.Len(t, gpus, 1)
return a.newServer(gpus, model, ggml, adapters, projectors, opts, numParallel)
}
slog.Info("a")
s.pendingReqCh <- a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
}
type mockLlm struct { type mockLlm struct {
pingResp error pingResp error
waitResp error waitResp error