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The code has been in production for the better part of a month now and helped dramatically collapse the code size and complexity in a way that I feel will be simple to maintain.
Combined metric Code size ×Cycle_count/Block _size.
ANSWER_CODE_SIZE Bytes value of the answer code size.
QUESTION_CODE_SIZE Bytes value of the question code size.
Then they also look at run-time, memory usage and code size.
The team also cut down on the code size and promises that meetings will load "instantly".
Although the simulation time is significantly reduced, it is still heavily affected by the code size.
Detailed implementation results (performance, code size, and FPGA resources utilization) are presented.
The hardware loop facility helps to gain higher program efficiency and reduces code size.
When code is irregular but still repetitive, hardware loops cannot be used to reduce code size.
Experimental results reveal substantial improvement in performance and code size compared to software compilers.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com