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On-chain finance just got a much bigger computer.
Today, Singularity is introducing G-SVM: a GPU-native execution engine for SVM programs.
G-SVM gives developers the programming model and tools they already know, with the capacity to run far more application activity in parallel.
This raises the ceiling for what can be built on-chain: larger markets, faster execution, real-time risk engines, more complex financial applications, and infrastructure capable of supporting global liquidity at far greater scale.
GPUs transformed AI by changing the amount of computation available to software.
G-SVM brings that shift to on-chain finance.
Today, Singularity is introducing G-SVM: a GPU-native execution engine for SVM programs.
G-SVM gives developers the programming model and tools they already know, with the capacity to run far more application activity in parallel.
This raises the ceiling for what can be built on-chain: larger markets, faster execution, real-time risk engines, more complex financial applications, and infrastructure capable of supporting global liquidity at far greater scale.
GPUs transformed AI by changing the amount of computation available to software.
G-SVM brings that shift to on-chain finance.
Introducing Rohu-Paplet Consensus from Singularity Research.
Rohu-Paplet is a novel mechanism addressing one of blockchain's longest-standing problems: achieving speed and resilience without sacrificing one for the other.
Today, nearly every consensus design commits to a single network assumption at genesis and carries it for life. However, this assumption often fails at scale.
For example, a synchronous design trusts a timeout that real latency will eventually violate, and when it does, the chain stalls right when it's needed most. On the other side, an asynchronous design survives that day but pays worst-case overhead on every block before it.
Rohu-Paplet reprices this assumption every block.
It brings 2未 finality while validators are responsive and coin-elected async rounds when they go quiet. The architecture measures network conditions every single block and adapts the read path while validators keep writing to one shared structure.
This Consensus buys two things most chains trade away: finality at the theoretical floor and a chain that keeps committing through the conditions that freeze anything built on a timeout.
This model ensures the protocol measures the network as it actually behaves, instead of guessing once and hoping the guess holds forever.
The team is currently preparing the full specification and first benchmarks for peer review.
Now back to the desks!
Rohu-Paplet is a novel mechanism addressing one of blockchain's longest-standing problems: achieving speed and resilience without sacrificing one for the other.
Today, nearly every consensus design commits to a single network assumption at genesis and carries it for life. However, this assumption often fails at scale.
For example, a synchronous design trusts a timeout that real latency will eventually violate, and when it does, the chain stalls right when it's needed most. On the other side, an asynchronous design survives that day but pays worst-case overhead on every block before it.
Rohu-Paplet reprices this assumption every block.
It brings 2未 finality while validators are responsive and coin-elected async rounds when they go quiet. The architecture measures network conditions every single block and adapts the read path while validators keep writing to one shared structure.
This Consensus buys two things most chains trade away: finality at the theoretical floor and a chain that keeps committing through the conditions that freeze anything built on a timeout.
This model ensures the protocol measures the network as it actually behaves, instead of guessing once and hoping the guess holds forever.
The team is currently preparing the full specification and first benchmarks for peer review.
Now back to the desks!
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