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Enable concurrency by default
This adjusts our default settings to enable multiple models and parallel requests to a single model. Users can still override these by the same env var settings as before. Parallel has a direct impact on num_ctx, which in turn can have a significant impact on small VRAM GPUs so this change also refines the algorithm so that when parallel is not explicitly set by the user, we try to find a reasonable default that fits the model on their GPU(s). As before, multiple models will only load concurrently if they fully fit in VRAM.
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@@ -77,7 +77,7 @@ func LoadModel(model string) (*GGML, error) {
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// NewLlamaServer will run a server for the given GPUs
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// The gpu list must be a single family.
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func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options) (LlamaServer, error) {
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func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options, numParallel int) (LlamaServer, error) {
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var err error
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var cpuRunner string
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var estimate MemoryEstimate
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@@ -213,8 +213,10 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
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// Windows CUDA should not use mmap for best performance
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// Linux with a model larger than free space, mmap leads to thrashing
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// For CPU loads we want the memory to be allocated, not FS cache
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if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == api.TriStateUndefined) ||
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(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == api.TriStateUndefined) ||
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(gpus[0].Library == "cpu" && opts.UseMMap == api.TriStateUndefined) ||
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opts.UseMMap == api.TriStateFalse {
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params = append(params, "--no-mmap")
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}
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@@ -227,15 +229,6 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
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params = append(params, "--numa")
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}
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numParallel := envconfig.NumParallel
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// TODO (jmorganca): multimodal models don't support parallel yet
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// see https://github.com/ollama/ollama/issues/4165
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if len(projectors) > 0 {
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numParallel = 1
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slog.Warn("multimodal models don't support parallel requests yet")
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}
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params = append(params, "--parallel", fmt.Sprintf("%d", numParallel))
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if estimate.TensorSplit != "" {
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