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kvcache: Pass granular cache size into implementations

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Currently the runner computes the kv size needed and creates a
cache of that size. This is the context size times number of
parallel sequences.

Cache implementations can make better decisions about their memory
usage, so instead pass in the required capacity, number of sequences
and maximum batch size. For now, the causal cache just uses this to
compute the size in the same way as before.
This commit is contained in:
Jesse Gross
2025-03-18 14:31:52 -07:00
committed by Jesse Gross
parent 6d1103048e
commit 3ed7ad3ab3
7 changed files with 44 additions and 32 deletions
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10
runner/ollamarunner/cache.go
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@@ -31,8 +31,10 @@ type InputCache struct {
cache kvcache.Cache
}
func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, multiUserCache bool) (*InputCache, error) {
if kvSize/int32(numSlots) < 1 {
func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, batchSize int, multiUserCache bool) (*InputCache, error) {
numCtx := kvSize / int32(numSlots)
if numCtx < 1 {
return nil, fmt.Errorf("must have at least one kv cache entry per parallel sequence (kv: %v parallel: %v)", kvSize, numSlots)
}
@@ -44,11 +46,11 @@ func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots
cache := model.Config().Cache
if cache != nil {
cache.Init(model.Backend(), kvCacheTypeFromStr(kvCacheType), kvSize)
cache.Init(model.Backend(), kvCacheTypeFromStr(kvCacheType), numSlots, int(numCtx), batchSize)
}
return &InputCache{
numCtx: kvSize / int32(numSlots),
numCtx: numCtx,
enabled: cache != nil,
slots: slots,
multiUserCache: multiUserCache,