Agenda  Compile-Time Rational Numbers  Durations  Clocks  Time Points  Dates  Time Zones 4 Agenda  Compile-Time Rational Numbers  Durations  Clocks  Time Points  Dates Dates  Time Zones5 Compile-Time Rational Numbers  Defined in  Work with rational numbers at compile time  Always normalized representation  Needed for durations in the library6 library6 Compile-Time Rational Numbers  Define a rational number: using r1 = ratio<1, 60>; // Represents 1/60  Retrieve numerator and denominator intmax_t num { r1::num }; intmax_t den { r1::den };

Gela Malek Pour gmalekpour@esri.com Visualize Time Enabled Data using ArcGIS Qt (C++) and ToolkitAbout Esri • We build mapping technology that our customers use to solve the world’s most complex challenges around the worldPurpose of this talk • Showcase a quick way to create a desktop app to visualize time enabled data • Setup the development environment using Esri templates • Use the ArcGIS toolkit to feature layer that include hurricane data as features • Each feature has a specific start time and end time in the feature table • We will use these start and end date values to draw and clear features

12 C++20’s Calendars and Time Zones in MSVC Miya Natsuhara ("MEE-yuh Not-soo-HAR-uh") Miya.Natsuhara@microsoft.com Software Engineer, Visual C++ LibrariesWelcome to CppCon 2021! Join Seconds • What are leap seconds? • How did we implement them in MSVC? • Part V: Time Zones • Overview of [time.zone] • IANA database challenges • Part VI: Conclusion7 Part I: Development Process8 • Code Review Videos! • clocks, clock_cast, leap_seconds (https://youtu.be/WX3OmVu4lAs) • time_zone and time_zone_link (https://youtu.be/MODhhr7m-5s) • system_clock::now(), file_clock, leap second awareness

numberOfValues) { for (int i { startValue }; i < startValue + numberOfValues; ++i) { time_t t { system_clock::to_time_t(system_clock::now()) }; cout << std::ctime(&t); co_yield i; } } int main() Concepts  Named requirements to constrain template parameters  Predicates evaluated at compile time21 Concepts  Example of a concept definition: template concept Incrementable = requires(T atomic_shared_ptr head; // in C++11: remove "atomic_" and use special // functions every time you touch head public: class reference { shared_ptr p; }; auto find(T

in_range(T t) noexcept;11 constexpr Algorithms12 C++20 constexpr Everything • constexpr enables compile-time programming without arcane templates • Algorithms: • P0202R3 constexpr And exchange() Example: lookup tables • Everyone uses lookup tables • Arrays are maximally space-efficient, very time-efficient • Sorted arrays: binary_search, lower_bound, equal_range • Now you can use constexpr algorithms More advanced: constexpr sort your lookup tables14 static_assert is_sorted • Compile-time evaluation = no run-time codegen, even in debug builds #include #include #include

RECEIVER OPERATION STATE connect start …operation completes… … and notifies receiver … time passes… Implementation details of some algorithm; e.g., then. then(sender, fn) -> sender22 SHAPE state start33 OPERATIONS EXECUTE OUTSIDE-IN Receiver Work is scheduled on the thread pool Time passes…. A thread in the pool picks up the work and executes it34 OPERATIONS EXECUTE OUTSIDE-IN Senders65 NO DETACHED COMPUTATION ALLOWED schedul e schedul e then then then schedul e when_al l time set_valu e set_valu e detached computation set_erro r set_erro r A thread in the thread

☑️�Just My Code debugging Demo C++20 in action Thu, Oct 28 – 10:30am C++20’s Calendars and Time Zones in MSVC Miya Natsuhara – `Online _4 Tue, Oct 26 – 10:30am Documentation in The Era of Concepts faster Unreal Engine 4.27.1 IntelliSense Ready 18x faster Learn more at http://aka.ms/18xfaster Link time 28x faster 5x faster 18x faster 1 2 3 0.00 100.00 200.00 300.00 400.00 500.00 600.00 76 62.86 59.00 26.72 26.25 22.90 Gears 5 Link Times (lower is better) Series1 Series2 Series3 Link Time in Seconds Performance of Visual Studio Developer inner-loop Build Debug Edit Find in

SolidKey PTS Provider Transform Sinker Transform PTS Provider Transform Sinker ● Batch Inserts ○ Time trigger ○ Number trigger ● Magical Flag PTS Magical Flag Quiz PTS Magical Flag Create PTS Sync multiple data source to Clickhouse in minutes BONUS Time travel history state Create Update Update Delete insert_id id name flag update_time UUID0 2 Bob1 2 2019-10-01 00:00:00 UUID1 2 Bob1.5 2 2019-10-01 12:00:00 UUID2 2 Bob2 2 2019-10-02 00:00:00 UUID3 2 Bob2 3 2019-10-03 00:00:00 BONUS Time travel history state Create Update Update Delete Future ● Auto configure through web ● Auto deploy

mode • Services are organized in hash table • IPVS DNAT • conntrack/iptables SNAT • Pros • O(1) time complexity in control/data plane • Stably runs for two decades • Support rich scheduling algorithm differ • Performance of a cluster in different time slot may differ • Due to CPU oversold • Suggestion: • Run the test against the same cluster during near time • Make CPU the bottleneck • 1 CPU handles

lack of machine time. How much of what software engineers now do is still devoted to the accidental, as opposed to the essential?”Agile Abstract “Therefore it appears that the time has come to address language can do is to furnish all the constructs the programmer imagines in the abstract program • Time-sharing • Preserves immediacy, and hence enables us to maintain an overview of complexity • Unified