The Goal - A Process of Ongoing Improvement Plot Summary Alex Rogo is a harried plant manager working ever more desperately to try improve performance. His factory is rapidly heading for disaster the market faster, we get an advantage in the marketplace. Process of on-going improvement “Everywhere, improvement was interpreted as almost synonymous to cost savings. People are concentrating on

● Other flag dances ● Dummy dynamic library to generate static libs NO LTOSummaryIncremental improvement ● Focus on improving new code; donʼt fix everything ● Incrementally adopt clang-format (clang-format-diff)

fundamental compute unit for many modern scientific computation, it is also a classic performance improvement problem to solve. Example: Feedforward propagation in neural network is done via matrix multiplication; fundamental compute unit for many modern scientific computation, it is also a classic performance improvement problem to solve. Example: Feedforward propagation in neural network is done via matrix multiplication; fundamental compute unit for many modern scientific computation, it is also a classic performance improvement problem to solve. Example: Feedforward propagation in neural network is done via matrix multiplication;

Kyuubi relies on Apache Spark to provide high-performance data query capabilities, and every improvement in the engine’s capabilities can help Kyuubi’s performance make a qualitative leap. Besides, Kyuubi Compared with HiveServer2, the most significant advantage of the first two should be the performance improvement. From the perspective of SQL syntax compatibility, Kyuubi and Spark Thrift Server are fully compatible Get Involved In the process of using Apache Kyuubi, if you have any questions, suggestions, or improvement ideas, you can participate in the Kyuubi community building through the following suggested channels

Kyuubi relies on Apache Spark to provide high-performance data query capabilities, and every improvement in the engine’s capabilities can help Kyuubi’s performance make a qualitative leap. Besides, Kyuubi Compared with HiveServer2, the most significant advantage of the first two should be the performance improvement. From the perspective of SQL syntax compatibility, Kyuubi and Spark Thrift Server are fully compatible Get Involved In the process of using Apache Kyuubi, if you have any questions, suggestions, or improvement ideas, you can participate in the Kyuubi community building through the following suggested channels

What if we could do “C++11 feels like a new language” again, for the whole language?5 Major improvement via directed evolution 10 simpler metric: 90% of today’s guidance not needed 50 safer incremental evolution-as-usual plan Default for existing evolution JS & other examples “10” improvement, leap-forward plan 10% 10 Status quo language (e.g., JavaScript, C++, Objective-C) C++ examples incremental evolution-as-usual plan Default for existing evolution JS & other examples “10” improvement, leap-forward plan 10% 10 Status quo language (e.g., JavaScript, C++, Objective-C) C++ examples

model to be considered feasible for deployment is a classification accuracy of 80%. Any additional improvement is not required, and we would prefer to choose the smallest model with best performance that meets as techniques that help you improve your model footprint. However, given that they lead to an improvement in quality metrics, we can use them to boost the performance of models that might have not been v/s epoch plot with the augmented data is shown in figure 3-6. The augmented run shows a clear improvement in validation accuracy throughout the training run. You must be wondering, how to revert to epoch

time required for these operations is almost zero. This represents a significant performance improvement over traditional serialization methods. Fanchen Su, XOffsetDatastructure, CppCon 2024 69 Algorithms implementation, we've chosen to use a Custom Allocator for two primary reasons: • Performance Improvement: • Our custom allocator is designed to provide faster allocations and deallocations compared implementation, we've chosen to use a Custom Allocator for two primary reasons: • Performance Improvement: • Our custom allocator is designed to provide faster allocations and deallocations compared

called it a comparator sanitizer We saw 7-8% perf improvement in production 75.2RESULTS We called it a comparator sanitizer We saw 7-8% perf improvement in production Reduced branch mispredictions a lot sanitizer We saw 7-8% perf improvement in production Reduced branch mispredictions a lot Fixed thousands of bugs 75.4RESULTS We called it a comparator sanitizer We saw 7-8% perf improvement in production Reduced bugs Fought the Hyrum's Law 75.5RESULTS We called it a comparator sanitizer We saw 7-8% perf improvement in production Reduced branch mispredictions a lot Fixed thousands of bugs Fought the Hyrum's Law

$0x3e8, %rdx jl .L1 php -dopcache.jit_debug=1 loop.php JUST-IN-TIME COMPILER · Over 100% Improvement In Bench VS PHP-7.2 BENCHMARK 0 3.5 7 10.5 14 PHP-5.0 PHP-5.1 PHP-5.2 PHP-5.3 PHP-5.4 PHP-5 0.048 0.104 0.077 0.01 0.01 0.01 0.022 PHP-7.2 PHP-JIT JUST-IN-TIME COMPILER · 7% Qps Improvement In Wordpress Homepage VS PHP-7.2 WORDPRESS HOMEPAGE BENCHMARK 0 100 200 300 400 PHP-5.0 Visible Improvement On Old Applications · Significant Improvement On Well-Written Codes · Type Inference Plays Very Important Role In Jit · More Type Info == More Performance Improvement · Use