v1-contracts VS homebrew-golem

If you're working on "large Ethereum smart contracts" you've missed the point. On chain logic should always be as minimal as possible. Uniswap v1 was two vyper files. One was 46 lines, and the other was 496 lines[1]. It took like 20 minutes to read through the code thoroughly, and was one of the most impactful contracts ever deployed to the network.

Solidity also matured a lot, which is why Uniswap v2 moved back. If you find yourself writing an EVM assembler from scratch, and you're trying to build something other than a compiler, you have veered way way off course, and need to re-evaluate your system architecture.

Feature creep might work well if you're trying to leech money from a government contract or something, or being paid by line of code you contribute, but it's fatal in the Ethereum world. I consulted for a number of projects that made the exact same mistake, and most of them aren't around anymore.

[1] https://github.com/Uniswap/uniswap-v1/tree/master/contracts

Golem, develop Docker applications and make use of their (now) very limited features. It's best suited for heavy calculations, or calculations you can split up between dozens or hundreds of nodes through sharding. A fork is working on bringing GPU & internet access, but it can be hard otherwise. They have a GLM Rewards Program that - generously rewards up to 20 users per month under regular conditions.

For compute, my experience has been the best with Akash, then Golem, then I have been unsuccessful with any other project as of yet. Both of these supports Docker images, but Golem is painfully thorough with securing providers with sandboxing in both networking and workloads. This makes Akash easier to use right now when wanting to run something more advanced such as a custom backend or a Minecraft Server.

If you want to run scientific calculations or similar, I highly recommend Golem. Right now, its best applications are ones that can scale by sharding, to use parallel computations. Think doing 100 similar small jobs on 100 computers instead of 1 large job on 1 computer. One average CPU-month costs $3.17, or you can rent 100 CPU-hours for $0.44. Notable examples are blender_cuda which runs on a GPU, and the entirety of awesome-golem.

Website: http://golem.network/

if you're not using your computer, you can consider letting other people use it! come checkout golem, a distributed super computer similar to Folding@Home, but for all kinds of computation not just protein research. You even earn some money and it's really easy to get started.

This is where the math of VPS on demand for testing vs home starts to matter. OR higher buy in but lower ongoing is SBC boards. Raspberry pi, turingpi, ION whatever boards from nvidia. All have higher cost, more limited abilities (in some ways) but FOR SURE are way lower power/heat than traditional low initial cost/higher ongoing. It's a common issue. Getting yourself a NAS or ESOS or SAN or whatever as an always on, mount it on the projects you need as storage. Depends on what you want, but an always on computer can do a hell of allot. golem.network, idle mining, BOINC for science, etc etc. Dunno, GLHF

It is public and been running for a bit now, seeing as you asked I assume its ok for me to say its golem.network ? Definitely open though if you want to join

Run a golem.network node to rent out some pi's to others who can purchase their compute power, isn't much but glad to help someone when I'm not using it