Jon Kalb retweeted
My CppCon keynote went really well!
Fun times talking about new memory hierarchies and the best ways we can programmatically prepare for them in advance.
Every Thursday immediately before CppCon, we invite members of the Denver C++ Meetup to join us for dinner at the Gaylord Rockies. (Note: Not everyone present is in the photo and not everyone in the photo was present.)
meetup.com/north-denver-metr…
Jon Kalb retweeted
The politics of the committee. The dedication of decades. The flow of solving the unsolvable, featuring some of "the brightest people you'll ever want to meet"
🎬 First audience preview screening
📅 September 16, 2026
📍 Exclusively for @CppCon attendees
youtu.be/87jvuDbnwqQ
#cpp
Jon Kalb retweeted
"If I were to tell a story about Boost, I'd start with the people."
Today we're sharing the official teaser for the Boost documentary. A film about the people, the politics, and the decades of work behind possibly the most important open source library you've never heard of 🎥👇
Jon Kalb retweeted
std::vector always heap allocates. std::array can't change size. For decades, there's been no standard container that gives you a dynamically sized array with a compile-time capacity limit and zero heap allocation
C++26 finally adds std::inplace_vector. Guess where they got the idea 🧵👇
Jon Kalb retweeted
I tried to stop std::hive.
When it became clear I couldn't, I tried to keep them for baking in a design that forced a particular implementation.
std::hive doesn't belong in the C++ standard library.
Jon Kalb retweeted
std::queue has no concept of concurrency. Wrap it in a mutex and every push serializes behind every pop: 16 cores fighting over one lock, 15 of them idle at any given time 🧵👇
Jon Kalb retweeted
Penn State + Lockheed Martin built a reinforcement-learning cognitive engine for @NASA and the @Space_Station in C++11
The engine manages real-time radio resource allocation across 6 competing objectives: bit error rate, throughput, bandwidth, spectral efficiency, transmit power efficiency, and DC power consumption
Two Boost libraries did the heavy lifting:
Boost.Asio: concurrent UDP listeners and raw Ethernet frame transmission to DVB-S2 modems, within a 40ms ground-to-orbit RTT constraint
Boost.Serialization: complete engine state (NN weights + training buffer) archived to disk between passes, so the radio resumes learning instead of starting over
20 live ISS flight passes. One of the first published cognitive engine experiments on a space-based asset
Learn more go.boost.org/4lWYXiY
Jon Kalb retweeted
The ISS passes over a ground station for a few minutes at a time. Your cognitive radio engine has that window to transmit and to learn. How do you preserve neural network state across orbital passes in C++? 🧵👇
Don’t hesitate. The conference itself won’t sell out, but our room block will and being in the main hotel is so much nicer than being in an overflow hotel.
Registration for CppCon 2026 is now open which will be held at the Gaylord Rockies in Aurora, Colorado from 12th-18th September.
cppcon.org/cppcon-2026-regis…
Check out our promotional video to find out what to expect!
youtu.be/8T71azsPTfE
#cpp #programming #coding
Jon Kalb retweeted
📣 The Boost formal review of Multi begins today
Multi, by Alfredo Correa, is a modern C++ library for manipulating and accessing data in multidimensional arrays, on both CPU and GPU memory
The review runs March 5–15, 2026. If you’re interested in a first look:
🔗 Code: github.com/correaa/boost-mul…
📖 Docs: correaa.github.io/boost-mult…
📬 To participate: lists.boost.org/archives/lis…
#cpp
Jon Kalb retweeted
Something's under review
A modern C++ library for multidimensional arrays, CPU and GPU, is being considered for inclusion in Boost 👇
Jon Kalb retweeted
Boost.Math now supports reverse mode automatic differentiation. Exact derivatives via computational graphs, no step size tuning, no approximation error. Thanks to Maksym Zhelyeznyakov (physics BS, applied math MS, ECE doctorate from UW), who hit this wall on a personal project
Now the same technique that powers gradient computation in PyTorch and TensorFlow is native in C++ through Boost. If you're building ML inference engines, trading systems, or physics simulations in C++, this changes your workflow
#cpp
Jon Kalb retweeted
If you're still using finite differences to compute gradients in C++, you're losing precision and performance. There's a better way now, thanks to a Boost contributor 🧵👇
Jon Kalb retweeted
Boost Blueprint 001: Compile-time Performance. Boost.Mp11 is arguably the fastest metaprogramming library in existence. It makes template heavy-lifting actually readable and lightning-fast.
Level up your C++ architecture. Follow @Boost_Libraries for the #BoostBlueprint series. 🚀
#cpp














