Equihash is an innovative proof-of-work algorithm that is designed to be efficient, ASIC-resistant, and memory-orientated. It powers well-known cryptocurrencies like Zcash and Bitcoin Gold and brings unique attributes compared to older PoW algorithms. Let’s examine equihash in-depth including its key features, working principle, and applications.
Overview of Equihash
Equihash was created in 2016 by Alex Biryukov and Dmitry Khovratovich from the University of Luxembourg. It represents a radically different approach to proof-of-work mining that aims to reduce the advantage of specialized ASIC hardware and favor more decentralized, GPU-based mining.
Some of the main design goals and features of Equihash include:
- ASIC-resistant to promote decentralized mining.
- Memory-hard requiring lots of RAM for mining.
- Efficient verification of PoW solution.
- Flexible difficulty tuning using parameter tweaking.
- Sparse matrix solving for mining proofs.
By requiring large memory sizes, Equihash enhances security and makes optimization trickier for ASIC devices. Let’s look at how it achieves this.
Working Principle of Equihash
The key innovation in Equihash is using memory-hard «proof-of-work» puzzles based on the generalized birthday problem. This involves finding collisions within a set of random cryptographic hash outputs.
The algorithm has two main parameters (N, K):
- N determines the memory requirement.
- K controls the computation/time tradeoff.
Miners start by generating a large set of random values based on the algorithm inputs. This seed output is stored in many GBs of RAM.
The next step involves recursively combining and reducing these values in layers using Wagner’s algorithm to find a colliding set of outputs. This is an extremely memory-intensive process.
Miners continuously repeat these steps and attempts to find a solution below the target difficulty. Equihash’s memory hardness delays any hardware optimizations.
Key Attributes and Benefits
Some of the standout benefits Equihash provides as a proof-of-work algorithm include:
- ASIC Resistance — Its memory hardness significantly slows and complicates ASIC development. This enhances decentralization.
- GPU Friendliness — Ordinary GPUs excel at the memory-intensive operations used in Equihash. This allows home PC miners to participate.
- Flexibility — The N,K parameters can be adjusted to tune mining difficulty and memory requirements.
- Security — Memory-hardness deters some machine learning optimization attacks and makes FPGA development expensive.
- Verification Efficiency — Equihash solutions can be verified quickly with minimal computation.
- Parallelization — The algorithm can scale efficiently across mining pools by parallelizing efforts.
Applications of Equihash
Equihash has emerged as a popular proof-of-work choice for new cryptocurrency projects looking to achieve ASIC resistance.
Some major coins that rely on Equihash include:
- Zcash — Privacy-focused currency that uses zk-SNARKs. First major adopter of Equihash.
- Bitcoin Gold — Bitcoin fork focused on GPU mining and decentralization.
- Komodo — All-in-one blockchain platform with smart contracts.
- ZenCash — Communications-centric crypto supporting anonymous messaging.
- Hush — Enhanced fork of Zcash using zk-SNARKs.
There are also Equihash minable tokens issued on networks like Ethereum Classic and Binance Smart Chain. The algorithm continues gaining popularity.
Equihash represents a clever and innovative approach to designing more decentralized, ASIC-resistant proof-of-work mining. By imposing memory hardness, it has succeeded in its goal of promoting GPU mining. The ability to fine-tune difficulty and memory requirements also makes Equihash flexible.
Looking ahead, Equihash appears positioned to remain an attractive choice for new cryptocurrencies aiming to launch with fair and accessible mining rewards. While no PoW is immune to ASICs forever, Equihash has proven robust and its principles continue to inspire memory-hard algorithm development. For these reasons, Equihash will likely remain influential for the foreseeable future.