In the blockchain and AI realm, where speed and efficiency are paramount, innovative solutions like Parallel Execution Scheduling (PES) are emerging as must-haves to maximise transactions per second (TPS). Without further ado, let's delve into the concept of PES, exploring its fundamental principles, its impact on blockchain scalability, and how it compares to another popular solution, sharding.
What is Parallel Execution Scheduling?
In traditional blockchain systems, transactions are processed sequentially, one after the other. This sequential execution can lead to bottlenecks, limiting the number of transactions that can be processed per second and hindering the overall scalability of the blockchain.
Parallel Execution Scheduling, as the name suggests, offers a revolutionary approach by enabling the concurrent processing of multiple transactions. This is akin to opening multiple checkout counters at a supermarket, allowing customers to be served simultaneously, thus reducing waiting times and increasing overall throughput.
The magic behind PES lies in its ability to identify transactions that do not conflict with each other and can be safely executed in parallel. This identification process often involves sophisticated algorithms and dependency analysis to ensure data integrity and prevent inconsistencies in the blockchain's state.
By harnessing the power of parallel execution, blockchains can significantly enhance their transaction processing capacity, opening the door to a new era of scalability and efficiency.
The Impact of Parallel Execution on Blockchain Scalability
Scalability has long been a major challenge for blockchain technology. As the number of users and transactions grows, the limitations of sequential processing become increasingly apparent. This can lead to network congestion, slower transaction confirmation times, and higher fees, hindering the widespread adoption of blockchain applications.
Parallel Execution Scheduling presents a powerful solution to this scalability dilemma. By processing multiple transactions simultaneously, PES can dramatically increase the throughput of a blockchain network, allowing it to handle a much larger volume of transactions per second. This enhanced capacity translates to faster transaction confirmations, reduced fees, and a smoother user experience.
Furthermore, the improved scalability facilitated by PES can pave the way for the development of more complex and resource-intensive blockchain applications. From decentralised finance (DeFi) platforms to supply chain management systems, PES empowers developers to create solutions that cater to a global audience without sacrificing performance or efficiency.
Parallel Execution vs. Sharding: A Comparison
While Parallel Execution Scheduling offers a promising approach to blockchain scalability, it is not the only solution available. Another popular technique is Sharding, which involves partitioning the blockchain network into smaller, more manageable shards, each responsible for processing a subset of transactions.
Both PES and Sharding aim to improve blockchain scalability, but they employ different strategies to achieve this goal. PES focuses on optimising transaction processing within a single blockchain, while Sharding distributes the workload across multiple shards.
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ACS2: aelf's Parallel Execution Standard
The aelf ACS2 standard facilitates parallel transaction execution on the blockchain. It requires contracts to implement the GetResourceInfo method, which specifies the state paths (keys in the database) that a transaction will read from or write to.
The system then uses this information to group transactions that don't conflict (i.e., don't access the same state paths) and execute them in parallel, improving overall throughput and efficiency.
For the full details, do check out our full documentation on ACS2.
The Next Big Standard: AI-Powered Parallel Execution
The fusion of artificial intelligence (AI) with parallel execution scheduling represents the next evolutionary leap in the effective upgrading of performance in AI layer 1 blockchains. While traditional Parallel Execution Scheduling (PES) focuses on identifying and executing non-conflicting transactions concurrently, AI-powered parallel execution (aPES) takes it a step further by leveraging AI algorithms to make more intelligent and dynamic scheduling decisions with Web3 and AI integrations.
What is AI Parallel Execution, and How Does it Differ from Traditional PES?
AI parallel execution employs machine learning and other AI techniques like Neural Network Prediction and Two-Stage Optimisation Process to predict transaction execution times, resource requirements, and potential conflicts. This allows for more precise and adaptive task scheduling, leading to improved resource utilisation and overall performance gains.
In contrast, traditional PES relies on static rules and heuristics to identify parallelisable transactions. While effective to a certain extent, this approach may not fully capture the dynamic nature of blockchain workloads and can lead to suboptimal scheduling decisions.
How Does aPES Work?
AI-powered parallel execution typically involves the following steps:
- Data Collection and Pre-processing: Historical transaction data, including execution times, resource usage, and dependencies, is collected and pre-processed to create a training dataset for AI models.
- AI Model Training: Machine learning algorithms, such as neural networks, are trained on the dataset to predict transaction characteristics and identify potential parallelisation opportunities.
- Real-time Scheduling: The trained AI models are used in real-time to analyse incoming transactions, predict their execution behavior, and make intelligent scheduling decisions to maximise parallelism and minimise conflicts.
- Continuous Learning and Adaptation: The AI models are continuously updated and refined based on new transaction data and feedback, ensuring that the scheduling system adapts to changing workload patterns and maintains optimal performance.
The Benefits and Importance of AI-Based Parallel Execution for aelf
aelf's aPES technology, an innovation that's set in the pipeline to complement its new AI-enabled blockchain infrastructure, is designed to address limitations and bottlenecks faced by blockchains today.
One example is the challenge of achieving high transaction throughput while maintaining low latency. Traditional consensus mechanisms, such as Proof-of-Work (PoW) used by Bitcoin, suffer from scalability limitations due to their sequential processing nature.
Here's where AI-Based Parallel Execution Scheduling comes into play. It leverages artificial intelligence algorithms to optimise the execution order of transactions in parallel, enabling multiple transactions to be processed simultaneously instead of one at a time.
By combining advanced AI algorithms with a robust parallel execution framework, aPES aims to deliver unparalleled performance and scalability for blockchain networks, especially for AI layer 1 blockchains like aelf.
AI-powered parallel execution offers several key benefits:
- Enhanced Performance: By making more informed scheduling decisions, AI can further increase transaction throughput, reduce latency, and improve overall system efficiency.
- Dynamic Adaptation: AI models can adapt to changing workload patterns and optimise scheduling in real-time, ensuring consistent performance even under varying conditions on blockchains with AI.
- Reduced Resource Waste: AI can help identify and prevent potential conflicts and bottlenecks, leading to more efficient resource utilisation and cost savings.
These benefits are crucial for AI layer 1 blockchain networks to achieve the scalability and performance required to support widespread adoption and meet the demands of real-world applications, using Web3 and AI integrations.
In Closing
By exploring and embracing these advancements, we can collectively contribute to the evolution of decentralised AI systems and unlock new levels of scalability and efficiency in blockchains with AI.
The future of blockchain technology lies in the convergence of AI and parallelisation, with innovative solutions like aelf's aPES leading the way towards a new era of high-speed, low-latency blockchains.
Experience increased efficiency using aelf's layer 1 blockchain for AI.
*Disclaimer: The information provided on this blog does not constitute investment advice, financial advice, trading advice, or any other form of professional advice. aelf makes no guarantees or warranties about the accuracy, completeness, or timeliness of the information on this blog. You should not make any investment decisions based solely on the information provided on this blog. You should always consult with a qualified financial or legal advisor before making any investment decisions.
About aelf
aelf, an AI-enhanced Layer 1 blockchain network, leverages the robust C# programming language for efficiency and scalability across its sophisticated multi-layered architecture. Founded in 2017 with its global hub in Singapore, aelf is a pioneer in the industry, leading Asia in evolving blockchain with state-of-the-art AI integration to ensure an efficient, low-cost, and highly secure platform that is both developer and end-user friendly. Aligned with its progressive vision, aelf is committed to fostering innovation within its ecosystem and advancing Web3 and AI technology adoption.
For more information about aelf, please refer to our Whitepaper V2.0.
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