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#Avalanche HyperSDK Research Deep Dive: π½π΄-π¨πππππππ, πΆπ-πππ-πππ, π·πππππππ π»ππππππππππ π¬ππππππππ
AFAIK HyperSDK is the FIRST build-a-chain SDK that runs txs in parallel for all Custom VMs out-of-the-box π
github.com/ava-labs/hypersdk/pull/560
So, you want to process 50k TPS on a blockchain?
Consider an "optimistic" world where data distribution is instantaneous+unbounded (if only π₯Ί) and block building/verification is perfectly pipelined (nodes spend the entire second verifying useful data)...
With serial execution, the average verification time of each transaction (including all block verification overhead, like root generation) cannot surpass **20 microseconds**.
Notice, this is an **upper bound** on the amortized block verification time allowed per tx.
While this target is possible to hit with optimized, pre-defined transaction types that are compiled into the VM (like TokenVM transfers) and lots of state caching, it is a pretty unrealistic requirement to hit when supporting complex, user-defined smart contracts/programs.
For example, WASM environment initialization (used in HyperSDK Programs) may take >= 20 microseconds alone.
Random disk reads (assuming no values needed for a tx are cached) can take ~10 microseconds-1ms depending on disk quality (NVMe -> SSD -> HDD) and value size.
So, what can be done?
As already demonstrated by @solana, @Aptos_Network, and @SuiNetwork in production, the path to supporting more complex interactions at scale is find a way to employ more cores during block building/verification to process non-conflicting txs in parallel.
Aside: Conflicts here are defined as >= 2 transactions attempting to read/write the same state.
Because blockchain execution must be deterministic, we must execute such transactions serially (based on block order) to ensure state transactions can be reproduced by all nodes.
If multiple transactions can be executed at once, in our example above, it greatly increases the average verification time each transaction can use while still hitting the same TPS.
This is particularly cool if concurrency can be scaled arbitrarily (more cores == more TPS).
If we have 16 cores of execution (and assume txs are non-conflicting), transactions could take ~320 microseconds of amortized execution to hit the 50k TPS target (in our "optimistic model").
This is a much more reasonable # for program execution (can be improved w/cores).
To support parallel execution for all transactions, the HyperSDK requires all transactions to enumerate the state keys they will read/write during processing.
With this info, an execution plan can be built on-the-fly to verify transactions (that may conflict) concurrently.
To generate these execution plans on-the-fly, I wrote the brand new "executor" package (which can sequence function execution over arbitrary, conflicting keys):
github.com/ava-labs/hypersdk/pull/559
Thanks to the flexibility of this package, concurrent transaction execution is supported on **both the build and verify path**.
MerkleDB concurrent read access allows us to also read keys from the disk concurrently now as well (further leveraging latent disk resources).
For those keeping track at home, the #Avalanche HyperSDK now has:
* WASM-Based Programs (i.e. smart contracts)
* Parallel Transaction Execution
* Multi-Dimensional Fees
* Nonce-Less Transactions
* Batch Signature Verification
* Deferred Root Generation
* Dynamic State Sync
During the remainder of the year, we will focus on continuing to optimize block data distribution + hardening everything for production-readiness (with a series of devnets).
If you want to get involved, check out the option HyperSDK issues: github.com/ava-labs/hypersdk/issues