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Hello, I would like to inquire whether the machine used for testing is still Amazon EC2 c5.xarge, or as mentioned in the question, whether the machine can support vector operations well. For example, the new feature added to JDK17 can be enabled by adding -- add modules=JDK.incubator. vector. However, if the hardware does not support it, it can actually cause the performance of the code that uses vector acceleration to decrease significantly (possibly by about 10 times) at runtime. If the hardware does not support vectors, can we consider removing the -- add modules=JDK.incubator. vector startup parameter.
The latest version of the wast library will enable partial vector acceleration based on whether -- add modules=jdk. incubator. vector has been added (which can normally accelerate by about 6%). If possible, could you please help run the results separately? Thank you very much!
./run deser --apis databind --libs wast --size 1000 --datatype users
The text was updated successfully, but these errors were encountered:
I don't know. But it sounds like something you can find out and report on (you actually have more info than me on this at this point since I wasn't even aware of this).
I'll run benchmarks on a single type of instance. Please let me know which you think is most capable/appropraite. Otherwise, I'll likely just pick the latest cX instance type next time.
I don't know. But it sounds like something you can find out and report on (you actually have more info than me on this at this point since I wasn't even aware of this).
I'll run benchmarks on a single type of instance. Please let me know which you think is most capable/appropraite. Otherwise, I'll likely just pick the latest cX instance type next time.
Can we run the above single test commands separately, adding --add-modules=jdk.incubator.vector to the startup parameter for the first time and not adding it for the second time? Let's see the results of the two runs. Generally, if the hardware supports vector acceleration, the first result will be better than the second one.
Hello, I would like to inquire whether the machine used for testing is still Amazon EC2 c5.xarge, or as mentioned in the question, whether the machine can support vector operations well. For example, the new feature added to JDK17 can be enabled by adding -- add modules=JDK.incubator. vector. However, if the hardware does not support it, it can actually cause the performance of the code that uses vector acceleration to decrease significantly (possibly by about 10 times) at runtime. If the hardware does not support vectors, can we consider removing the -- add modules=JDK.incubator. vector startup parameter.
The latest version of the wast library will enable partial vector acceleration based on whether -- add modules=jdk. incubator. vector has been added (which can normally accelerate by about 6%). If possible, could you please help run the results separately? Thank you very much!
./run deser --apis databind --libs wast --size 1000 --datatype users
The text was updated successfully, but these errors were encountered: