Fuel Labs Profile picture
Sep 6 14 tweets 7 min read
Today, we're proud to announce $80M of support led by @blockchaincap and @stratosxyz!

Fuel is the fastest Modular Execution Layer delivering the highest flexible throughput with maximum security guarantees for the Ethereum ecosystem.

fuel-labs.ghost.io/fuel-labs-anno…
Blockchains are still not globally accessible and available. Scaling compute remains a road block.

Fuel aims to change this by using the power of modular design, new thinking around blockchain processing and new kinds of tools empowering developers like never before.
Currently, there is a massive shift happening in L1s. The industry is moving away from monolithic and towards modular design, where execution is separated from data availability and consensus. Image
This separation allows for specialization at each layer, delivering a significant increase in both bandwidth and execution capacity across the stack. Fuel is designed specifically to leverage additional bandwidth in ways no other scalability system can.
Fuel demonstrates that launching monolithic L1s in 2022 are short-sighted and that building high performance execution layers on top of modular blockchains can produce extremely high throughput with incredible Ethereum-grade security guarantees. Image
What is a Modular Execution Layer (or MEL)?

We define it as: a verifiable computation system designed for the modular blockchain stack. This differs from layer-2s which are typically optimized and designed for monolithic constraints.
We believe achieving global adoption does not require launching new L1s, but instead can happen at the execution layer. Innovation on both the VM level and language level (Sway) is happening on Ethereum through Fuel!

github.com/FuelLabs/fuel-…
Sway is a Rust-inspired smart contract language that delivers a powerful, vertically-integrated developer experience designed for safety and efficiency.

Follow @SwayLang for more!
Moreover, Fuel includes fraud-provable trust-minimized light clients that deliver better security and decentralization guarantees, in addition to trust-minimized liquidity bridging, which is not possible between two independent L1s. Image
There are three central pillars to Fuel’s technology stack:

⏩ Parallel transaction execution. More compute. More state access.

🛠️ The Fuel Virtual Machine (FuelVM). Less waste. More flexibility.

🌴 A superior developer experience (with @SwayLang and Forc). Powerful. Sleek.
Put simply, Fuel specializes in making execution as efficient as possible. Image
Now is a good time for a shout-out to each and every one of our contributors, who go above and beyond to take us #BeyondMonolithic. Image
Our vision is to build the engine for the autonomous future, powering the next generation of independent human coordination and cooperation.

Every computation matters.

fuel.network

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More from @fuellabs_

Apr 26
What is a Modular Execution Layer? Let's dissect, a 🧵
Fuel defines a Modular Execution Layer as:

"A verifiable computation system designed for the modular blockchain stack."

More concretely, a fraud- or validity-provable blockchain (or other computation system) that leverages a modular blockchain for data availability.
Why is modular execution important?

L2s built on monolithic chains have failed to keep costs low. This is because current rollups optimize for the small amount of DA capacity provided by the monolithic present rather than the enormous capacity available in the modular future.
Read 7 tweets
Mar 24, 2020
⛽ Today we’re proud to release the first public version of Yul+, new low-level language for Ethereum!

Yul+ makes writing stateless contracts (including optimistic rollups) easier and increases code legibility.

medium.com/@fuellabs/intr…
🔪 Why is this needed? Solidity doesn’t support pass-by-reference or slices.

This means parsing Merkle branches/proofs---a key component of stateless contracts---is wastefully expensive if written in Solidity.
➕ Yul+ adds a number of QoL improvements, such as enums, constants, Booleans, and by-default safemath. But most importantly, it adds in-memory structures.

This means structured calldata can be parsed *in-place* (no memory copies, no problems!).
Read 5 tweets

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