devcon 5 / yul ewasm solidity progress and future plans
Duration: 00:19:31
Speaker: Christian Reitwiessner
Type: Breakout
Expertise: Advanced
Event: Devcon
Date: Invalid Date
Categories
Understanding the Ethereum Blockchain Protocol
Ethereum's Vitalik Buterin presents on the intricacies of the Ethereum Blockchain Protocol.
Optimization techniques for EVM implementations
A number of optimization techniques for Ethereum Virtual Machine implementations are going to be presented along with examples and benchmarks based on evmone and EVMJIT projects. Based on performed benchmarks, the presentation will show ~10x speed improvements in evmone comparing to other EVM implementations. While evmone is build in C++, the optimizations are not limited to C++. All of the optimizations are applicable to any compiled language, some of them even to interpreted languages.
Ethereum for Dummies
Ethereum's CTO Dr. Gavin Wood presents "Ethereum for Dummies" or "So, now we've built it, WTF is it?"
Ethereum in 25 Minutes, Version MMXVII
So what are all of the different moving parts of the Ethereum blockchain? What are uncles, how do contracts call other contracts, who runs them? What is the role of proof of work and proof of stake, and what exactly is gas? What will EIP86 do for you? Vitalik Buterin provides a 25-minute technical overview of the ethereum blockchain, start to finish, and explain many of these concepts in detail.
K Semantic Model of Beacon Chain
Daejun Park gives an overview of the K-Semantic Model of the Beacon Chain.
Complexities in Aggregation at Scale
Mikhail Kalinin presents Complexities in Aggregation at Scale.
Anatomy of an Ethereum Client
The overview of the building blocks of an Ethereum client: what any client implementation should have. A practical perspective on how Ethereum works under the hood.
The EVM: Leaner, Meaner, and Closer to the Metal
Dr. Greg Colvin gives their talk titled, "The EVM: Leaner, Meaner, and Closer to the Metal"
Using Ethereum for Secure Decentralized Optimization
We demonstrate how complicated optimization problems can be solved by combining decentralized optimization algorithms with an aggregation step in a smart contract. Using tools from convex optimization, we decompose difficult problems into a set of subproblems with can be computed off-blockchain, finally reaching consensus on the global optimum by passing message with the on-blockchain aggregation step. We present an example of applying this approach to optimizing power dispatch on an electricity grid, but the approach can also be used to solve other problems in machine learning, coordinating robotic agents, or coordinating economic systems.
Verifying Casper
Why you can be certain that the four slashing conditions of Casper are enough to catch forks.