TinyUFO is a fast and efficient in-memory cache. It adopts the state-of-the-art S3-FIFO as well as TinyLFU algorithms to achieve high throughput and high hit ratio as the same time.
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We compare TinyUFO with lru, the most commonly used cache algorithm and moka, another great cache library that implements TinyLFU.
The table below show the cache hit ratio of the compared algorithm under different size of cache, zipf=1.
cache size / total assets | TinyUFO | TinyUFO - LRU | TinyUFO - moka (TinyLFU) |
---|---|---|---|
0.5% | 45.26% | +14.21pp | -0.33pp |
1% | 52.35% | +13.19pp | +1.69pp |
5% | 68.89% | +10.14pp | +1.91pp |
10% | 75.98% | +8.39pp | +1.59pp |
25% | 85.34% | +5.39pp | +0.95pp |
Both TinyUFO and moka greatly improves hit ratio from lru. TinyUFO is the one better in this workload. This paper contains more thorough cache performance evaluations S3-FIFO, which TinyUFO varies from, against many caching algorithms under a variety of workloads.
The table below shows the number of operations performed per second for each cache library. The tests are performed using 8 threads on a x64 Linux desktop.
Setup | TinyUFO | LRU | moka |
---|---|---|---|
Pure read | 148.7 million ops | 7.0 million ops | 14.1 million ops |
Mixed read/write | 80.9 million ops | 6.8 million ops | 16.6 million ops |
Because of TinyUFO's lock-free design, it greatly outperforms the others.
TinyUFO provides a compact mode to trade raw read speed for more memory efficiency. Whether the saving worthy the trade off depends on the actual size and the work load. For small in-memory assets, the saved memory means more things can be cached.
The table below show the memory allocation (in bytes) of the compared cache library under certain workloads to store zero-sized assets.
cache size | TinyUFO | TinyUFO compact | LRU | moka |
---|---|---|---|---|
100 | 39,409 | 19,000 | 9,408 | 354,376 |
1000 | 236,053 | 86,352 | 128,512 | 535,888 |
10000 | 2,290,635 | 766,024 | 1,075,648 | 2,489,088 |