Alibaba's MNN Deep Learning Framework Continues Squeezing More Performance
Alibaba developers released an updated version of their "blazing fast" lightweight deep learning framework MNN, or the Mobile Neural Network.
This deep learning framework that has been "battle-tested by business-critical use cases in Alibaba" continues working to exploit every bit of possible performance.
With the 1.1.1 release noting more optimizations for "speed up" as well as bug fixes, our MNN test profile for benchmarking with the Phoronix Test Suite and OpenBenchmarking.org was updated against the new version.
Indeed, we are seeing some nice speed-ups compared to the state of the code just a few months ago:
Inception V3 was the main outlier with mixed results across the systems tested.
More performance numbers can be found via MNN on OpenBenchmarking.org. See how your system performs with Alibaba's deep learning framework by running phoronix-test-suite benchmark mnn.
This deep learning framework that has been "battle-tested by business-critical use cases in Alibaba" continues working to exploit every bit of possible performance.
With the 1.1.1 release noting more optimizations for "speed up" as well as bug fixes, our MNN test profile for benchmarking with the Phoronix Test Suite and OpenBenchmarking.org was updated against the new version.
Indeed, we are seeing some nice speed-ups compared to the state of the code just a few months ago:
Inception V3 was the main outlier with mixed results across the systems tested.
More performance numbers can be found via MNN on OpenBenchmarking.org. See how your system performs with Alibaba's deep learning framework by running phoronix-test-suite benchmark mnn.
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