Deep dive on a proper benchmarking and implementation for 1M task on the Erlang runtime. Clearly the previous benchmark had room for improvements.

Indeed, the story of integrating C and C++ with Rust isn't a simple one right now. It might introduce larger attack surfaces. Some improvements are proposed in this paper.

Everything you always wanted to know but didn't dare asking about memory allocators. OK, maybe not "everything everything" but this gives a very good overview on how they work and the trade-offs they have to make.

Doesn't give the whole picture (memory isn't the only important parameter) but interesting results nonetheless. A few surprises in there, Java and C# do much better than one might assume for instance.

Often overlooked in test cases. Still it's not that complicated to setup.

Interesting approach. There's still a lot we can achieve with static analysis in those good old languages.

I very much agree with this. It is a real concern with our industry, we seem indeed to keep reinventing the wheel a lot. How do we stop forgetting? How do we move forward?

Interesting set of memory patterns. Didn't know all of them, some are definitely useful and I already use, I'll try to look for the others next time I need to.

Very good overview about RAII, ownership, borrowing references. All that comparing C++ and Rust in their ways to handle those concepts. Definitely a must-read even though it's a bit long.

Good explanation of the relationship between memory and learning... it's not quite what one would intuitively think, things need to be in long-term memory first which means you need to repeat things somehow so that they end up there (otherwise they're just in the temporary working memory).

OK, it's 2022 and this is still not an adequate ecosystem for system programming.

Excellent deepdive about pipes, on the path to optimization we see how perf is used, how memory is managed by the kernel etc. Very thorough.

That looks like a very interesting tool for larger Python based projects. Definitely need a way to profile memory use in there.

Since the tooling is still far from great for web frontend memory analysis, it's nice to see some effort there.

Interesting research on how relying on digital systems reshape our memory and our perception of our own abilities.

Interesting exploration of an easy to introduce memory leak in frontend code.

At last some interesting tooling for profiling memory usage of web frontends. Clearly this is very early days though, this will get more interesting as the tooling makes progress. Some of the numbers in the benchmarks they came up with in this article are very scary though.

Interesting piece covering: how a memory allocator works, why it can be slow, how to use it the best way possible and how to pick an allocator for your project.