neerajsi

I had a family friend working on diamond semiconductors in the 90s. The application at that time was for sensors located in the hot section of a jet engine.

Only the ia64 version of the jit was based on msvc. And older versions of aot mode. Not the more typical jit targets.

I believe the new enabling technology for better codegen is tiered compilation, which has only been around for a couple years.

No. Genetic diversity and natural selection have created many intricate, beautiful, and useful structures. Unless someone is willing to argue that Darwinian selection is sentient, it's clear that theres at least one non sentient process that is creative.

I agree. I think the problem is shared context. A good human writer estimates their audience's understanding and writes close to their level. The llm doesn't know this for any particular audience and falls back to a static trained baseline or some other incorrect level.

I hope we'll have some kind of good paradigm to do lora style learning or maybe an output subagent or something so we can better calibrate the output style in a fuzzy way. In context learning (instructions, memories) doesn't currently seem that effective.

I was curious about whether one of the count bits instructions can help. Of course I'm lazy now and asked an llm to check... The llm noticed that the articles solution includes a floating point subtract in the end. This is fine since the target is wasm which has fsub/fadd, but was initially odd to see in a floating point emulator.

Apparently a ctz solution is a bit longer, but doesn't cross from the floating to integer domain at all, so might be better in the overall algorithm. There are hidden implicit floating to int convert instructions.

This was a really cool little problem!

That's a more effective strategy in the primaries. It doesn't make much sense in the general. Hopefully your district isn't all that close.

Fwiw on the compiler front, I used to work on the msvc tool chain. It has been doing lto (aka ltcg) for a very long time at reasonably good throughput. That tool chain also has done incremental compilation on a per function basis for about 7 years. Sharing header parsing across translation units has been possible through PCH for decades. Even without PCH, inline header functions only get codegened once in ltcg mode (not counting inline expansion).

In a large multi-dll build like Windows or Office, the import/export information across modules is computed without doing codegen, so ltcg codegen can be done in parallel regardless of the module dependency graph.

I never worked deeply in the build systems for Linux based OSes or other unixes, but I gather that some symbol visibility choices make the build situation worse in Unix systems than Windows.

We call those doctors with less medical school and training ARNPs. I've seen several and they seem to do well for basic needs.

Not to mention if you have kids there are more limited options for their schooling and extracurriculars in a rural area.

It seemed to be ai assisted writing, but it was still interesting to me.

This is surprisingly apt to me. Fertilizer is apparently one of the fundamental geopolitical dependencies on capital and access to petrochemicals. Solving fertilizer would unlock a huge amount of human potential in the Global South.

Disallowing smc is a significant perf/power win. For cpus that run a large variety of large code (e.g. a web browser or ux stack), being able to cache a large instruction footprint and fetch/decode it quickly is important. Having to have the icache snoop data writes and entangle the i-fetch with the store buffer machinery would be a huge penalty to pay for a niche use case. Unlike loads, which are a small fraction of instructions to disambiguate with stores, you'd have to disambiguate every single instruction.

JIT is important to Apple platforms, and they seem to manage to make it work well enough even with the need for explicit invalidation.

Yes, I think it's a problem for society. Death in old age frees up social, economic, physical, and political resources for the next generation of the living. If the rich and powerful escape death, because after all they will the people with the resources to do so, society will lose the adaptability and natural change that comes from new generations taking the reins.

I think macro economics has provided significant value to society even if the model isn't precise with perfect predictions. We do have worthwhile models that the government can use to avoid making serious monetary mistakes in the face of the real business cycle. We are unlikely to trigger the awful depths of the great depression again.

The main problem I see with public economists is Goodharts law: When the predictive model becomes visible to the agents in the economy, there are stable strategies to counteract those models. So if economists want to remain good predictors of real outcomes, they have to collect massive amounts of data to feed the model but then remain mostly invisible afterward, so that the agents being analyzed don't change behavior too much.

In some sense, a known bad model that is used to set central policy may be good because the rest of the economic agents can work on a diversity of better models without correlating as much with each other and the known central model.