Blockchain technology has the potential to revolutionize many industries due to its decentralized, transparent, and secure nature. However, blockchain platforms face major scalability challenges that limit their widespread adoption. Most blockchains can only process a small number of transactions per second compared to the massive throughput required by global financial and enterprise systems.

Parallelization Refers to Simultaneous Processing

Parallelization is a computing technique that focuses on the simultaneous execution of tasks to enhance overall performance and efficiency. It involves breaking up a large process into smaller fragments that can be run concurrently across multiple processors or machines.
In parallelized systems, multiple central processing units (CPUs) or computers work together to tackle different parts of a workload at the same time. This contrasts with sequential processing, where operations take place one after another on a single processor.

Why Parallelization is Needed for Blockchain

Public blockchains achieve decentralized consensus and security by having every node validate and record all transactions on the network. However, this creates a major bottleneck that severely restricts transaction throughput. For instance, the Bitcoin network supports less than 10 transactions per second while global payment leaders like Visa handle over 65,000 transactions per second.

Simply adding more transactions to a block does not help because each block must be propagated across the entire network before the next one is created. At a certain point, larger blocks take too long to transmit between nodes. This limits how fast new transactions can be validated across the blockchain.

Parallelization breaks through this bottleneck by enabling transaction validation to occur across multiple processors simultaneously. This means consensus and blockchain updates can happen much faster.

Advantages of a Parallelized Blockchain

There are several key advantages that parallelization provides for blockchain platforms:

• Greatly Increased Transaction Speed: Parallel processing can enable thousands more transactions per second. This is essential for consumer and enterprise adoption.
• Scalability: Blockchains must scale up to meet higher demand without compromising decentralization or security. Parallelization enables horizontal scaling where more nodes can be added.
• Lower Latency: Simultaneous validation across the network significantly reduces confirmation times and latency for each transaction.
• Efficiency: Parallel execution saves time and energy by preventing processing queue build ups. This further incentivizes the network.

Key Parallelization Methods for Blockchain

There are two primary approaches to introducing parallelization to blockchains – on-chain and off-chain solutions.

On-Chain Parallelization

This refers to modifications made directly to the core blockchain protocol to allow faster processing:

• Sharding: This technique breaks the blockchain into separate shards or fragments with each verifying a portion of transactions in parallel. Popular platforms like Ethereum 2.0 employ sharding.
• Alternative Consensus Models: New consensus models like proof-of-stake and directed acyclic graphs (DAGs) enable parallel transaction verification across the distributed network of nodes and miners.
• Block Partitioning: This involves dividing a single block into separate partitions that can be verified in parallel by different miners to gain efficiency.

Off-Chain Parallelization

Off-chain solutions handle parallel processing outside the main blockchain:

• Sidechains: Transactions are validated on separate sidechains running in parallel before being settled back to the main blockchain. This avoids its limitations.
• State Channels: Nodes interact via multi-signature accounts on the blockchain but conduct transfers off-chain. The final netted result is updated on-chain.
• Plasma Chains: This framework enables complex logic and parallel processing to occur on interconnected child chains with only essential data relayed to the parent chain.

Real-World Examples of Parallelized Blockchains

There are already prominent blockchain projects employing parallelization:

• Ethereum: Ethereum 2.0 introduces sharding which creates 64 parallel chains to increase throughput.
• Zilliqa: This blockchain uses network sharding allowing it to process over 2,000 transactions per second as more nodes join the network.
• Harmony: Harmony sharding partitions the network communication and transaction validation into different shards while employing a fast Byzantine fault tolerance algorithm.
• Ontology: Ontology uses a modular design with multiple blockchains achieving consensus in parallel through a VBFT algorithm.
• IoTeX: IoTeX utilizes block partitioning to introduce intra-block parallelization combined with their Roll-DPoS consensus for faster transaction confirmation.

Conclusion

In conclusion, parallelization solutions introduce concurrent processing capabilities to blockchain networks enabling them to validate transactions simultaneously rather than sequentially. This allows modern blockchain platforms to scale up to meet enterprise demand without compromising decentralization or security. Both on-chain and off-chain methods like sharding, alternative consensus models, sidechains and state channels provide much higher throughput, lower latency, faster confirmations and greater efficiency vital for real-world adoption. Leading next-generation blockchain projects have already incorporated parallelization, setting the stage for the technology to power large-scale decentralized applications in the future.