Merge pull request #768 from jmorganca/mxyng/bytes

fix memory check

api/client.go

@@ -14,6 +14,7 @@ import (
 	"runtime"
 	"strings"
 
+	"github.com/jmorganca/ollama/format"
 	"github.com/jmorganca/ollama/version"
 )
 
@@ -127,7 +128,7 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	return nil
 }
 
-const maxBufferSize = 512 * 1000 // 512KB
+const maxBufferSize = 512 * format.KiloByte
 
 func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
 	var buf *bytes.Buffer

format/bytes.go

@@ -2,14 +2,21 @@ package format
 
 import "fmt"
 
+const (
+	Byte     = 1
+	KiloByte = Byte * 1000
+	MegaByte = KiloByte * 1000
+	GigaByte = MegaByte * 1000
+)
+
 func HumanBytes(b int64) string {
 	switch {
-	case b > 1000*1000*1000:
-		return fmt.Sprintf("%d GB", b/1000/1000/1000)
-	case b > 1000*1000:
-		return fmt.Sprintf("%d MB", b/1000/1000)
-	case b > 1000:
-		return fmt.Sprintf("%d KB", b/1000)
+	case b > GigaByte:
+		return fmt.Sprintf("%d GB", b/GigaByte)
+	case b > MegaByte:
+		return fmt.Sprintf("%d MB", b/MegaByte)
+	case b > KiloByte:
+		return fmt.Sprintf("%d KB", b/KiloByte)
 	default:
 		return fmt.Sprintf("%d B", b)
 	}

llm/llama.go

@@ -24,6 +24,7 @@ import (
 	"time"
 
 	"github.com/jmorganca/ollama/api"
+	"github.com/jmorganca/ollama/format"
 )
 
 //go:embed llama.cpp/*/build/*/bin/*
@@ -197,7 +198,7 @@ type llama struct {
 
 var errNoGPU = errors.New("nvidia-smi command failed")
 
-// CheckVRAM returns the available VRAM in MiB on Linux machines with NVIDIA GPUs
+// CheckVRAM returns the free VRAM in bytes on Linux machines with NVIDIA GPUs
 func CheckVRAM() (int64, error) {
 	cmd := exec.Command("nvidia-smi", "--query-gpu=memory.free", "--format=csv,noheader,nounits")
 	var stdout bytes.Buffer
@@ -207,7 +208,7 @@ func CheckVRAM() (int64, error) {
 		return 0, errNoGPU
 	}
 
-	var free int64
+	var freeMiB int64
 	scanner := bufio.NewScanner(&stdout)
 	for scanner.Scan() {
 		line := scanner.Text()
@@ -216,15 +217,16 @@ func CheckVRAM() (int64, error) {
 			return 0, fmt.Errorf("failed to parse available VRAM: %v", err)
 		}
 
-		free += vram
+		freeMiB += vram
 	}
 
-	if free*1024*1024 < 2*1000*1000*1000 {
+	freeBytes := freeMiB * 1024 * 1024
+	if freeBytes < 2*format.GigaByte {
 		log.Printf("less than 2 GB VRAM available, falling back to CPU only")
-		free = 0
+		freeMiB = 0
 	}
 
-	return free, nil
+	return freeBytes, nil
 }
 
 func NumGPU(numLayer, fileSizeBytes int64, opts api.Options) int {
@@ -232,7 +234,7 @@ func NumGPU(numLayer, fileSizeBytes int64, opts api.Options) int {
 		return opts.NumGPU
 	}
 	if runtime.GOOS == "linux" {
-		vramMib, err := CheckVRAM()
+		freeBytes, err := CheckVRAM()
 		if err != nil {
 			if err.Error() != "nvidia-smi command failed" {
 				log.Print(err.Error())
@@ -241,15 +243,13 @@ func NumGPU(numLayer, fileSizeBytes int64, opts api.Options) int {
 			return 0
 		}
 
-		freeVramBytes := int64(vramMib) * 1024 * 1024 // 1 MiB = 1024^2 bytes
-
 		// Calculate bytes per layer
 		// TODO: this is a rough heuristic, better would be to calculate this based on number of layers and context size
 		bytesPerLayer := fileSizeBytes / numLayer
 
 		// max number of layers we can fit in VRAM, subtract 8% to prevent consuming all available VRAM and running out of memory
-		layers := int(freeVramBytes/bytesPerLayer) * 92 / 100
-		log.Printf("%d MiB VRAM available, loading up to %d GPU layers", vramMib, layers)
+		layers := int(freeBytes/bytesPerLayer) * 92 / 100
+		log.Printf("%d MiB VRAM available, loading up to %d GPU layers", freeBytes, layers)
 
 		return layers
 	}
@@ -509,7 +509,7 @@ type PredictRequest struct {
 	Stop             []string `json:"stop,omitempty"`
 }
 
-const maxBufferSize = 512 * 1000 // 512KB
+const maxBufferSize = 512 * format.KiloByte
 
 func (llm *llama) Predict(ctx context.Context, prevContext []int, prompt string, fn func(api.GenerateResponse)) error {
 	prevConvo, err := llm.Decode(ctx, prevContext)

llm/llm.go

@@ -10,6 +10,7 @@ import (
 	"github.com/pbnjay/memory"
 
 	"github.com/jmorganca/ollama/api"
+	"github.com/jmorganca/ollama/format"
 )
 
 type LLM interface {
@@ -55,39 +56,30 @@ func New(workDir, model string, adapters []string, opts api.Options) (LLM, error
 				opts.NumGPU = 0
 			}
 		}
-	}
 
-	totalResidentMemory := memory.TotalMemory()
-	switch ggml.ModelType() {
-	case "3B", "7B":
-		if ggml.FileType() == "F16" && totalResidentMemory < 16*1000*1000 {
-			return nil, fmt.Errorf("F16 model requires at least 16 GB of memory")
-		} else if totalResidentMemory < 8*1000*1000 {
-			return nil, fmt.Errorf("model requires at least 8 GB of memory")
-		}
-	case "13B":
-		if ggml.FileType() == "F16" && totalResidentMemory < 32*1000*1000 {
-			return nil, fmt.Errorf("F16 model requires at least 32 GB of memory")
-		} else if totalResidentMemory < 16*1000*1000 {
-			return nil, fmt.Errorf("model requires at least 16 GB of memory")
-		}
-	case "30B", "34B", "40B":
-		if ggml.FileType() == "F16" && totalResidentMemory < 64*1000*1000 {
-			return nil, fmt.Errorf("F16 model requires at least 64 GB of memory")
-		} else if totalResidentMemory < 32*1000*1000 {
-			return nil, fmt.Errorf("model requires at least 32 GB of memory")
-		}
-	case "65B", "70B":
-		if ggml.FileType() == "F16" && totalResidentMemory < 128*1000*1000 {
-			return nil, fmt.Errorf("F16 model requires at least 128 GB of memory")
-		} else if totalResidentMemory < 64*1000*1000 {
-			return nil, fmt.Errorf("model requires at least 64 GB of memory")
+		var requiredMemory int64
+		var f16Multiplier int64 = 2
+
+		switch ggml.ModelType() {
+		case "3B", "7B":
+			requiredMemory = 8 * format.GigaByte
+		case "13B":
+			requiredMemory = 16 * format.GigaByte
+		case "30B", "34B", "40B":
+			requiredMemory = 32 * format.GigaByte
+		case "65B", "70B":
+			requiredMemory = 64 * format.GigaByte
+		case "180B":
+			requiredMemory = 128 * format.GigaByte
+			f16Multiplier = 4
 		}
-	case "180B":
-		if ggml.FileType() == "F16" && totalResidentMemory < 512*1000*1000 {
-			return nil, fmt.Errorf("F16 model requires at least 512GB of memory")
-		} else if totalResidentMemory < 128*1000*1000 {
-			return nil, fmt.Errorf("model requires at least 128GB of memory")
+
+		systemMemory := int64(memory.TotalMemory())
+
+		if ggml.FileType() == "F16" && requiredMemory*f16Multiplier > systemMemory {
+			return nil, fmt.Errorf("F16 model requires at least %s of total memory", format.HumanBytes(requiredMemory))
+		} else if requiredMemory > systemMemory {
+			return nil, fmt.Errorf("model requires at least %s of total memory", format.HumanBytes(requiredMemory))
 		}
 	}