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0 pointsfalcolas6y ago0 comments

So long as an application needs to share state between worker processes, (database, redis cluster, etc) then Amdahl’s law still applies. There’s very few modern applications that can truly scale linearly.

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imtringued6y ago

You're confusing something. Fully consistent databases are primarily limited by the speed of communication because they need to replicate writes and queries to all nodes and wait for a response even if a node is on the other side of the planet. Unless your CPU is extremely slow (clock frequencies of a few kilo Herz) the speed of light is a significantly more important limit. This is actually a usecase where modern CPUs are more than fast enough and we don't need a significant improvement in processing speed. Faster storage and networks are welcome though.

pdimitar6y ago

As a guy using a 10-core Xeon workstation with 64GB 2666Mhz DDR4 ECC RAM and a NVMe SSD capable of 2.8 GB/s read and write... I have to tell you that I only partially agree.

I've noticed my compilation speeds got dramatically better (compared to a MacBook Pro and an old-ish i7-3770 desktop PC). And it can handle even the sluggishness of Slack just fine without you noticing a lag, which I view as a huge achievement.

However, one thing my very detailed system monitors are telling me every day is -- 99% of all software we use every day is not parallel enough. So I have this amazingly powerful CPU that only (1) Git garbage collection, (2) PostgreSQL restoring a big backup, (3) Rust compiler and (4) [partially] Elixir compiler can saturate to its full potential.

I'd say that if everybody buys the new AMD Threadrippers and PCIe 4.0 motherboards, RAMs, SSDs and GPUs, we'd all be collectively fine for like 10 years.

The software however, it badly needs more parallel processing baked in it.

dnautics6y ago

Share consistent state. Eventually consistent models (most web apps) are often generally okay.

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