Opinionated Framework for Building Hyper-Scalable Blockchains on Avalanche
The freedom to create your own Virtual Machine (VM), or blockchain runtime, is one of the most exciting and powerful aspects of building on Avalanche, however, it is difficult and time-intensive to do from scratch. Forking existing Avalanche VMs makes it easier to get started, like spacesvm or subnet-evm, but is time-consuming and complex to ensure correctness as changes occur upstream (in repos which often weren't meant to be used as a library).
The hypersdk is the first (of many) frameworks dedicated to making it
faster, safer, and easier to launch your own optimized blockchain on an Avalanche
Subnet. By hiding much of the complexity of building your own blockchain
runtime behind Avalanche-optimized data structures and algorithms, the
hypersdk enables builders to focus their attention on the aspects of their
runtime that make their project unique (and override the defaults only if needed).
For example, a DEX-based project should focus on implementing a novel trading
system and not on transaction serialization, assuming that is already done
efficiently for them.
This opinionated design methodology means that most runtimes built on the
hypersdk, called a hypervm, only need to implement 500-1000 lines of their own
code to add custom interaction patterns (and don't need to copy-paste code from upstream
that they need to keep up-to-date). However, if you do want to provide your own
mechanism, you can always override anything you are using upstream if you can
compose something better suited for your application. That same DEX-based
project may wish to implement custom block building logic that prioritizes the
inclusions of trades of certain partners or that interact with certain order
books.
Last but certainly not least, the usage of these Avalanche-optimized data structures
and algorithms means that your hyperchain can process thousands of transactions per second
without needing to hire a team of engineers to optimize it or understanding
anything about how it works under the hood...but you can certainly achieve
higher throughput if you do ;).
hypersdk: framework for building high-performance blockchains on Avalanchehypervm: Avalanche Virtual Machine built using thehypersdkhyperchain:hypervmdeployed on the Avalanche Network
hypersdk is considered ALPHA software and is not safe to use in
production. The framework is under active development and may change
significantly over the coming months as its modules are optimized and
audited.
All hypersdk state is stored using x/merkledb,
a path-based merkelized radix tree implementation provided by avalanchego. This high-performance
data structure minimizes the on-disk footprint of any hypervm out-of-the-box by deleting
any data that is no longer part of the current state (without performing any costly reference counting).
The use of this type of data structure in the blockchain context was pioneered by the go-ethereum team in an effort to minimize the on-disk footprint of the EVM. We wanted to give a Huge shoutout to that team for all the work they put into researching this approach.
Instead of requiring nodes to execute all previous transactions when joining
any hyperchain (which may not be possible if there is very high throughput on a Subnet),
the hypersdk just syncs the most recent state from the network. To avoid falling
behind the network while syncing this state, the hypersdk acts as an Avalanche Lite
Client and performs consensus on newly processed blocks without verifying them (updating its
state sync target whenever a new block is accepted).
The hypersdk relies on x/sync,
a bandwidth-aware dynamic sync implementation provided by avalanchego, to
sync to the tip of any hyperchain.
The hypersdk defaults to only storing what is necessary to build/verify the next block
and to help new nodes sync the current state (not execute historical state transitions).
If the hypersdk did not limit block storage growth, the disk requirements for validators
would grow at an alarming rate each day (making running any hypervm impractical).
Consider the simple example where we process 25k transactions per second (assume each
transaction is ~400 bytes); this would require the hypersdk to store 10MB per
second (not including any overhead in the database for doing so). This works out to
864GB per day or 315.4TB per year.
When MinimumBlockGap=250ms (minimum time between blocks), the hypersdk must store at
least ~240 blocks to allow for the entire ValidityWindow to be backfilled (otherwise
a fully-synced, restarting hypervm will not become "ready" until it accepts a block at
least ValidityWindow after the last accepted block). To provide some room for error during
disaster recovery (network outage), however, it is recommended to configure the hypersdk to
store the last >= ~50,000 accepted blocks (~3.5 hours of activity with a 250ms MinimumBlockGap).
This allows archival nodes that become disconnected from the network (due to a data center outage or bug)
to ensure they can persist all historical blocks (which would otherwise be deleted by all participants and
unindexable).
The number of blocks that the hypersdk stores on-disk, the AcceptedBlockWindow, can be tuned by any hypervm
to an arbitrary depth (or set to MaxInt to keep all blocks). To limit disk IO used to serve blocks over
the P2P network, hypervms can configure AcceptedBlockWindowCache to store recent blocks in memory.
In the hypersdk, smart contracts
(e.g. programs that run on blockchains) are referred to simply as programs. Programs
are WASM-based binaries that can be invoked during block
execution to perform arbitrary state transitions. This is a more flexible, yet less performant,
alternative to defining all Auth and/or Actions that can be invoked in the hypervm in the
hypervm's code (like the tokenvm).
Because the hypersdk can execute arbitrary WASM, any language (Rust, C, C++, Zig, etc.) that can
be compiled to WASM can be used to write programs. You can view a collection of
Rust-based programs here.
The hypersdk provides out-of-the-box support for arbitrary transaction authorization logic.
Each hypersdk transaction includes an Auth object that implements an
Actor function (identity that participates in an Action) and a Sponsor function (identity
that pays fees). These two identities could be the same (if using a simple signature
verification Auth module) but may be different (if using a "gas relayer" Auth module).
Auth modules may be hardcoded, like in
morpheusvm and
tokenvm, or execute
a program (i.e. a custom deployed multi-sig). To allow for easy interaction between different
Auth modules (and to ensure Auth modules can't interfere with each other), the
hypersdk employs a standard, 33-byte addressing scheme: <typeID><ids.ID>. Transaction
verification ensures that any Actor and Sponsor returned by an Auth module
must have the same <typeID> as the module generating an address. The 32-byte hash (<ids.ID>)
is used to uniquely identify accounts within an Auth scheme. For programs, this
will likely be the txID when the program was deployed and will be the hash
of the public key for pure cryptographic primitives (the indirect benefit of this
is that account public keys are obfuscated until used).
Because transaction IDs are used to prevent replay, it is critical that any signatures used
in Auth are not malleable.
If malleable signatures are used, it would be trivial for an attacker to generate additional, valid
transactions from an existing transaction and submit it to the network (duplicating whatever Action was
specified by the sender).
It is up to each Auth module to limit the computational complexity of Auth.Verify() to prevent a DoS
(invalid Auth will not charge Auth.Sponsor()).
The hypersdk is primarily about an obsession with hyper-speed and
hyper-scalability (and making it easy for developers to achieve both by
wrapping their work in opinionated and performant abstractions).
Developers don't care how easy it is to launch or maintain their own
blockchain if it can't process thousands of transactions per second with low
time-to-finality. For this reason, most development time on the hypersdk
thus far has been dedicated to making block verification and state management
as fast and efficient as possible, which both play a large role in making this
happen.
hypersdk transactions must specify the keys they will access in state (read
and/or write) during authentication and execution so that non-conflicting transactions
can be processed in parallel. To do this efficiently, the hypersdk uses
the executor package, which
can generate an execution plan for a set of transactions on-the-fly (no preprocessing required).
executor is used to parallelize execution in both block building and in block verification.
When a hypervm's Auth and Actions are simple and pre-specified (like in the morpheusvm),
the primary benefit of parallel execution is to concurrently fetch the state needed for execution
(actual execution of precompiled golang only takes nanoseconds). However, parallel execution
massively speeds up the E2E execution of a block of programs, which may each take a few milliseconds
to process. Consider the simple scenario where a program takes 2 milliseconds; processing 1000 programs
in serial would take 2 seconds (far too long for a high-throughput blockchain). The same execution, however,
would only take 125 milliseconds if run over 16 cores (assuming no conflicts).
The number of cores that the hypersdk allocates to execution can be tuned by
any hypervm using the TransactionExecutionCores configuration.
All hypersdk blocks include a state root to support dynamic state sync. In dynamic
state sync, the state target is updated to the root of the last accepted block while
the sync is ongoing instead of staying pinned to the last accepted root when the sync
started. Root block inclusion means consensus can be used to select the next state
target to sync to instead of using some less secure, out-of-consensus mechanism (i.e.
Avalanche Lite Client).
Dynamic state sync is required for high-throughput blockchains because it relieves the nodes that serve state sync queries from storing all historical state revisions (if a node doesn't update its sync target, any node serving requests would need to store revisions for at least as long as it takes to complete a sync, which may require significantly more storage).
type StatefulBlock struct {
Prnt ids.ID `json:"parent"`
Tmstmp int64 `json:"timestamp"`
Hght uint64 `json:"height"`
Txs []*Transaction `json:"txs"`
StateRoot ids.ID `json:"stateRoot"`
}Most blockchains that store a state root in the block use the root of a merkle tree of state post-execution, however, this requires waiting for state merklization to complete before block verification can finish. If merklization was fast, this wouldn't be an issue, however, this process is typically the most time consuming aspect of block verification.
hypersdk blocks instead include the merkle root of the post-execution state of a block's
parent rather than a merkle root of their own post-execution state. This design enables the
hypersdk to generate the merkle root of a block's post-execution state asynchronously
while the consensus engine is working on other tasks that typically are network-bound rather
than CPU-bound, like merklization, making better use of all available resources.
The Auth interface (detailed below) exposes a function called AsyncVerify that
the hypersdk may call concurrently (may invoke on other transactions in the same
block) at any time prior to/during block execution. Most hypervms perform signature
verification in this function and save any state lookups for the full Auth.Verify
(which has access to state, unlike AsyncVerify). The generic support for performing certain
stateless activities during execution can greatly reduce the e2e verification
time of a block when running on powerful hardware.
Some public-key signature systems, like Ed25519, provide
support for verifying batches of signatures (which can be much more efficient than
verifying each signature individually). The hypersdk generically supports this
capability for any Auth module that implements the AuthBatchVerifier interface,
even parallelizing batch computation for systems that only use a single-thread to
verify a batch.
Instead of mapping transaction resource usage to a one-dimensional unit (i.e. "gas"
or "fuel"), the hypersdk utilizes five independently parameterized unit dimensions
(bandwidth, compute, storage[read], storage[allocate], storage[write]) to meter
activity on each hypervm. Each unit dimension has a unique metering schedule
(i.e. how many units each resource interaction costs), target, and max utilization
per rolling 10 second window.
When network resources are independently metered, they can be granularly priced
and thus better utilized by network participants. Consider a simple example of a
one-dimensional fee mechanism where each byte is 2 units, each compute cycle is 5 units,
each storage operation is 10 units, target usage is 7,500 units per block, and the max
usage in any block is 10,000 units. If someone were to use 5,000 bytes of block data
without utilizing any CPU/storing data in state, they would exhaust the block capacity
without using 2 of the 3 available resources. This block would also increase the price
of each unit because usage is above the target. As a result, the price to use compute
and storage in the next block would be more expensive although neither has been used.
In the hypersdk, only the price of bandwidth would go up and the price of CPU/storage
would stay constant, a better reflection of supply/demand for each resource.
So, why go through all this trouble? Accurate and granular resource metering is required to safely increase the throughput of a blockchain. Without such an approach, designers need to either overprovision the network to allow for one resource to be utilized to maximum capacity (max compute unit usage may also allow unsustainable state growth) or bound capacity to a level that leaves most resources unused. If you are interested in reading more analysis of multidimensional fee pricing, Dynamic Pricing for Non-fungible Resources: Designing Multidimensional Blockchain Fee Markets is a great resource.
Developers must have to implement a ton of complex code to take advantage of this fee mechanism, right? Nope!
Multidimensional fees are abstracted away from hypervm developers and managed
entirely by the hypersdk. hypervm designers return the fee schedule, targets,
and max usage to use in Rules (allows values to change depending on timestamp) and
the hypersdk will handle the rest:
GetMinUnitPrice() Dimensions
GetUnitPriceChangeDenominator() Dimensions
GetWindowTargetUnits() Dimensions
GetMaxBlockUnits() Dimensions
GetFeeMarketPriceChangeDenominator() uint64
GetFeeMarketWindowTargetUnits() uint64
GetFeeMarketMinUnitPrice() uint64
GetBaseComputeUnits() uint64
GetStorageKeyReadUnits() uint64
GetStorageValueReadUnits() uint64 // per chunk
GetStorageKeyAllocateUnits() uint64
GetStorageValueAllocateUnits() uint64 // per chunk
GetStorageKeyWriteUnits() uint64
GetStorageValueWriteUnits() uint64 // per chunkAn example configuration may look something like:
MinUnitPrice: chain.Dimensions{100, 100, 100, 100, 100},
UnitPriceChangeDenominator: chain.Dimensions{48, 48, 48, 48, 48},
WindowTargetUnits: chain.Dimensions{20_000_000, 1_000, 1_000, 1_000, 1_000},
MaxBlockUnits: chain.Dimensions{1_800_000, 2_000, 2_000, 2_000, 2_000},
// Fee Market Parameters
FeeMarketMinUnits: 100,
FeeMarketWindowTargetUnits: 600 * 1024,
FeeMarketPriceChangeDenominator: 48,
BaseComputeUnits: 1,
StorageKeyReadUnits: 5,
StorageValueReadUnits: 2,
StorageKeyAllocateUnits: 20,
StorageValueAllocateUnits: 5,
StorageKeyWriteUnits: 10,
StorageValueWriteUnits: 3,Historically, one of the largest barriers to supporting multidimensional fees has been the complex UX it can impose on users. Setting a one-dimensional unit price and max unit usage already confuses most, how could you even consider adding more?
The hypersdk takes a unique approach and requires users to set a
single Base.MaxFee field, denominated in tokens rather than usage.
The hypersdk uses this fee to determine whether or not a transaction
can be executed and then only charges what it actually used. For
example, a user may specify to use up to 5 TKN but may only be charged
1 TKN, depending on their transaction's unit usage and the price of
each unit dimension during execution. This approach is only possible
because the hypersdk requires transactions to be "fully specified"
before execution (i.e. an executor can determine the maximum amount
of units that will be used by each resource without simulating the
transaction).
It is important to note that the resource precomputation can be quite
pessimistic (i.e. assumes the worst) and can lead to the maximum fee
for a transaction being ~2x as large as the fee it uses on-chain (depending
on the usage of cold/warm storage, as discussed later). In practice,
this means that accounts may need a larger balance than they otherwise
would to issue transactions (as the MaxFee must be payable during
execution). In the future, it will also be possible to optionally
specify a max usage of each unit dimension to better bound this pessimism.
Transactions are executed in FIFO order by each validator and there is no
way for a user to specify some "priority" fee to have their transaction
included in a block sooner. If a transaction cannot be executed when
it is pulled from the mempool (because its MaxFee is insufficient), it will
be dropped and must be reissued.
Aside from FIFO handling being dramatically more efficient for each validator,
price-sorted mempools are not particularly useful in high-throughput
blockchains where the expected mempool size is ~0 or there is a bounded transaction
lifetime (60 seconds by default on the hypersdk).
To make the multidimensional fee implementation for the hypersdk simpler,
it would have been possible to unify all storage operations (read, allocate,
write) into a single unit dimension. We opted not to go this route, however,
because hypervm designers often wish to regulate state growth much differently
than state reads or state writes.
Fundamentally, it makes sense to combine resource usage into a single unit dimension if different operations are scaled substitutes of each other (an executor could translate between X units of one operation to Y units of another). It is not clear how to compare, for example, the verification of a signature with the storage of a new key in state but is clear how to compare the verification of a signature with the addition of two numbers (just different CPU cycle counts).
Although more nuanced, the addition of new data to state is a categorically different operation than reading data from state and cannot be compared on a single plane. In other words, it is not clear how many reads a developer would or should trade for writes and/or that they are substitutes for each other in some sort of disk resource (by mapping to a single unit dimension, performing a bunch of reads would make writes more expensive).
To compute the maximum amount of storage units that a transaction could use,
it must be possible to determine how much data a particular key can read/write
from/to state. The hypersdk requires that all state keys are suffixed with
a big-endian encoded uint16 of the number of "chunks" (each chunk is 64 bytes)
that can be read/stored to satisfy this requirement. This appended size suffix is part of the key,
so the same key with different size suffixes would be considered distinct keys.
This constraint is equivalent to deciding whether to use a uint8, uint16, uint32,
uint64, etc. when storing an unsigned integer value in memory. The tighter a
hypervm developer bounds the max chunks to the chunks they will store, the cheaper
the estimate will be for a user to interact with state. Users are only charged, however,
based on the amount of chunks actually read/written from/to state.
hypersdk transactions don't use nonces
to protect against replay attack like many other account-based blockchains. This means users
can submit transactions concurrently from a single account without worrying about ordering them properly
or getting stuck on a transaction that was dropped by the mempool.
Additionally, hypersdk transactions contain a time past which they can no longer be included inside
of a hypersdk block. This makes it straightforward to take advantage of temporary situations on a
hyperchain (if you only wanted your transaction to be valid for a few seconds) and removes
the need to broadcast replacement transactions (if the fee changes or you want
to cancel a transaction).
On the performance side of things, a lack of transaction nonces makes the mempool more performant (as we no longer need to maintain multiple transactions for a single account and ensure they are ordered) and makes the network layer more efficient (we can gossip any valid transaction to any node instead of just the transactions for each account that can be executed at the moment).
Each hypersdk transaction specifies an array of Actions that
must all execute successfully for any state changes to be committed.
Additionally, each Action is permitted to return an array of outputs (each
output is arbitrary bytes defined by the hypervm) upon successful execution.
The tokenvm uses Action batches to offer complex, atomic interactions over simple
primitives (i.e. create order, fill order, and cancel order). For example, a user
can create a transaction that fills 8 orders. If any of the fills fail, all pending
state changes in the transaction are rolled back. The tokenvm uses Action outputs to
return the remaining units on any partially filled order to power an in-memory orderbook.
The outcome of execution is not stored/indexed by the hypersdk. Unlike most other
blockchains/blockchain frameworks, which provide an optional "archival mode" for historical access,
the hypersdk only stores what is necessary to validate the next valid block and to help new nodes
sync to the current state. Rather, the hypersdk invokes the hypervm with all execution
results whenever a block is accepted for it to perform arbitrary operations (as
required by a developer's use case). In this callback, a hypervm could store
results in a SQL database or write to a Kafka stream.
Every object that can appear on-chain (i.e. Actions and/or Auth) and every chain
parameter (i.e. Unit Price) is scoped by block timestamp. This makes it
possible to easily modify existing rules (like how much people pay for certain
types of transactions) or even disable certain types of Actions altogether.
Launching your own blockchain is the first step of a long journey of continuous evolution. Making it straightforward and explicit to activate/deactivate any feature or config is critical to making this evolution safely.
Unlike the Virtual Machines live on the Avalanche Primary Network (which gossip
transactions uniformly to all validators), the hypersdk only gossips
transactions to the next few preferred block proposers (using Snowman++'s
lookahead logic).
This change greatly reduces the amount of unnecessary transaction gossip
(which we define as gossiping a transaction to a node that will not produce
a block during a transaction's validity period) for any hyperchain out-of-the-box.
If you prefer to employ a different gossiping mechanism (that may be more
aligned with the Actions you define in your hypervm), you can always
override the default gossip technique with your own. For example, you may wish
to not have any node-to-node gossip and just require validators to propose
blocks only with the transactions they've received over RPC.
When initializing a hypervm, the developer explicitly specifies which storage backends
to use for each object type (state vs blocks vs metadata). As noted above, this
defaults to CockroachDB's pebble but can be swapped with experimental storage
backends and/or traditional cloud infrastructure. For example, a hypervm
developer may wish to manage state objects (for the Path-Based Merkelized Radix
Tree) on-disk but use S3 to store blocks and PostgreSQL to store transaction metadata.
Unlike other VMs on Avalanche, hypervms produce blocks continuously (even if empty).
While this may sound wasteful, it improves the "worst case" AWM verification cost (AWM verification
requires creating a reverse diff to the last referenced P-Chain block), prevents a fallback to leaderless
block production (which can lead to more rejected blocks), and avoids a prolonged post-bootstrap
readiness wait (hypersdk waits to mark itself as ready until it has seen a ValidityWindow of blocks).
Looking ahead, support for continuous block production paves the way for the introduction of chain/validator-driven actions, which should be included on-chain every X seconds (like a price oracle update) regardless of how many user-submitted transactions are present.
It is functionally impossible to improve the performance of any runtime without
detailed metrics and comprehensive tracing. For this reason, the hypersdk
provides both to any hypervm out-of-the-box. These metrics and traces are
aggregated by avalanchego and can be accessed using the
/ext/metrics
endpoint. Additionally, all logs in the hypersdk use the standard avalanchego logger
and are stored alongside all other runtime logs. The unification of all of
these functions with avalanchego means existing avalanchego monitoring tools
work out of the box on your hypervm.
We've created three hypervm examples, of increasing complexity, that demonstrate what you
can build with the hypersdk (with more on the way).
When you are ready to build your own hypervm, we recommend using the morpheusvm as a template!
Who is Morpheus ("The Matrix")?
The morpheusvm provides the first glimpse into the world of the hypersdk.
After learning how to implement native token transfers in a hypervm (one of the simplest Custom VMs
you could make), you will have the choice to go deeper (red pill) or to turn back to the VMs that you
already know (blue pill).
To ensure the hypersdk remains reliable as we optimize and evolve the codebase,
we also run E2E tests in the morpheusvm on each PR to the hypersdk core modules.
We created the tokenvm to showcase how to use the
hypersdk in an application most readers are already familiar with, token minting
and token trading.
The tokenvm lets anyone create any asset, mint more of
their asset, modify the metadata of their asset (if they reveal some info), and
burn their asset. Additionally, there is an embedded on-chain exchange that
allows anyone to create orders and fill (partial) orders of anyone else. To
make this example easy to play with, the tokenvm also bundles a powerful CLI
tool and serves RPC requests for trades out of an in-memory order book it
maintains by syncing blocks. If you are interested in the intersection of
exchanges and blockchains, it is definitely worth a read (the logic for filling
orders is < 100 lines of code!).
To ensure the hypersdk remains reliable as we optimize and evolve the codebase,
we also run E2E tests in the tokenvm on each PR to the hypersdk core modules.
The indexvm will be rewritten using the new WASM Programs module.
The indexvm is much more complex than
the tokenvm (more elaborate mechanisms and a new use case you may not be
familiar with). It was built during the design of the hypersdk to test out the
limits of the abstractions for building complex on-chain mechanisms. We recommend
taking a look at this hypervm once you already have familiarity with the hypersdk to gain an
even deeper understanding of how you can build a complex runtime on top of the hypersdk.
The indexvm is dedicated to increasing the usefulness of the world's
content-addressable data (like IPFS) by enabling anyone to "index it" by
providing useful annotations (i.e. ratings, abuse reports, etc.) on it.
Think up/down vote on any static file on the decentralized web.
The transparent data feed generated by interactions on the indexvm can
then be used by any third-party (or yourself) to build an AI/recommender
system to curate things people might find interesting, based on their
previous interactions/annotations.
Less technical plz? Think TikTok/StumbleUpon over arbitrary IPFS data (like NFTs) but all your previous likes (across all services you've ever used) can be used to generate the next content recommendation for you.
The fastest way to expedite the transition to a decentralized web is to make it
more fun and more useful than the existing web. The indexvm hopes to play
a small part in this movement by making it easier for anyone to generate
world-class recommendations for anyone on the internet, even if you've never
interacted with them before.
We'll use both of these hypervms to explain how to use the hypersdk below.
To use the hypersdk, you must import it into your own hypervm and implement the
required interfaces. Below, we'll cover some of the ones that your
hypervm must implement.
Note:
hypersdkrequires a minimum Go version of 1.21
type Controller interface {
Initialize(
inner *VM, // hypersdk VM
snowCtx *snow.Context,
gatherer ametrics.MultiGatherer,
genesisBytes []byte,
upgradeBytes []byte,
configBytes []byte,
) (
config Config,
genesis Genesis,
builder builder.Builder,
gossiper gossiper.Gossiper,
vmDB database.Database,
stateDB database.Database,
handler Handlers,
actionRegistry chain.ActionRegistry,
authRegistry chain.AuthRegistry,
authEngines map[uint8]AuthEngine,
err error,
)
Rules(t int64) chain.Rules // ms
// StateManager is used by the VM to request keys to store required
// information in state (without clobbering things the Controller is
// storing).
StateManager() chain.StateManager
// Anything that the VM wishes to store outside of state or blocks must be
// recorded here
Accepted(ctx context.Context, blk *chain.StatelessBlock) error
Rejected(ctx context.Context, blk *chain.StatelessBlock) error
// Shutdown should be used by the [Controller] to terminate any async
// processes it may be running in the background. It is invoked when
// `vm.Shutdown` is called.
Shutdown(context.Context) error
}The Controller is the entry point of any hypervm. It initializes the data
structures utilized by the hypersdk and handles both Accepted and
Rejected block callbacks. Most hypervms use the default Builder,
Gossiper, Handlers, and Database packages so this is typically a lot of
boilerplate code.
You can view what this looks like in the tokenvm by clicking this
link.
ActionRegistry *codec.TypeParser[Action, bool]
AuthRegistry *codec.TypeParser[Auth, bool]The ActionRegistry and AuthRegistry inform the hypersdk how to
marshal/unmarshal bytes on-the-wire. If the Controller did not provide these,
the hypersdk would not know how to extract anything from the bytes it was
provided by the Avalanche Consensus Engine.
In the future, we will provide an option to automatically marshal/unmarshal
objects if an ActionRegistry and/or AuthRegistry is not provided using
a default codec.
type Genesis interface {
Load(context.Context, atrace.Tracer, state.Mutable) error
}Genesis is typically the list of initial balances that accounts have at the
start of the network and a list of default configurations that exist at the
start of the network (fee price, enabled txs, etc.). The serialized genesis of
any hyperchain is persisted on the P-Chain for anyone to see when the network
is created.
You can view what this looks like in the tokenvm by clicking this
link.
type Action interface {
Object
// ComputeUnits is the amount of compute required to call [Execute]. This is used to determine
// whether the [Action] can be included in a given block and to compute the required fee to execute.
ComputeUnits(codec.Address, Rules) uint64
// StateKeysMaxChunks is used to estimate the fee a transaction should pay. It includes the max
// chunks each state key could use without requiring the state keys to actually be provided (may
// not be known until execution).
StateKeysMaxChunks() []uint16
// StateKeys is a full enumeration of all database keys that could be touched during execution
// of an [Action]. This is used to prefetch state and will be used to parallelize execution (making
// an execution tree is trivial).
//
// All keys specified must be suffixed with the number of chunks that could ever be read from that
// key (formatted as a big-endian uint16). This is used to automatically calculate storage usage.
//
// If any key is removed and then re-created, this will count as a creation instead of a modification.
StateKeys(actor codec.Address, actionID ids.ID) state.Keys
NMTNamespace() []byte
UseFeeMarket() bool
// Execute actually runs the [Action]. Any state changes that the [Action] performs should
// be done here.
//
// If any keys are touched during [Execute] that are not specified in [StateKeys], the transaction
// will revert and the max fee will be charged.
//
// If [Execute] returns an error, execution will halt and any state changes will revert.
Execute(
ctx context.Context,
r Rules,
mu state.Mutable,
timestamp int64,
actor codec.Address,
actionID ids.ID,
) (outputs [][]byte, err error)
}Actions are the heart of any hypervm. They define how users interact with
the blockchain runtime. Specifically, they are "user-defined" element of
any hypersdk transaction that is processed by all participants of any
hyperchain.
You can view what a simple transfer Action looks like here
and what a more complex "fill order" Action looks like here.
type Result struct {
Success bool
Error []byte
Outputs [][][]byte
// Computing [Units] requires access to [StateManager], so it is returned
// to make life easier for indexers.
Units fees.Dimensions
Fee uint64
}Actions emit a Result at the end of their execution. This Result
indicates if the execution was a Success (if not, all effects are rolled
back), how many Units were used (failed execution may not use all units an
Action requested), an Output (arbitrary bytes specific to the hypervm).
type Auth interface {
Object
// ComputeUnits is the amount of compute required to call [Verify]. This is
// used to determine whether [Auth] can be included in a given block and to compute
// the required fee to execute.
ComputeUnits(Rules) uint64
// Verify is run concurrently during transaction verification. It may not be run by the time
// a transaction is executed but will be checked before a [Transaction] is considered successful.
// Verify is typically used to perform cryptographic operations.
Verify(ctx context.Context, msg []byte) error
// Actor is the subject of the [Action] signed.
//
// To avoid collisions with other [Auth] modules, this must be prefixed
// by the [TypeID].
Actor() codec.Address
// Sponsor is the fee payer of the [Action] signed.
//
// If the [Actor] is not the same as [Sponsor], it is likely that the [Actor] signature
// is wrapped by the [Sponsor] signature. It is important that the [Actor], in this case,
// signs the [Sponsor] address or else their transaction could be replayed.
//
// TODO: add a standard sponsor wrapper auth (but this does not need to be handled natively)
//
// To avoid collisions with other [Auth] modules, this must be prefixed
// by the [TypeID].
Sponsor() codec.Address
}The Auth mechanism is arguably the most powerful core module of the
hypersdk because it lets the builder create arbitrary authentication rules
that align with their goals.
type Rules interface {
// Should almost always be constant (unless there is a fork of
// a live network)
NetworkID() uint32
ChainID() ids.ID
GetMinBlockGap() int64 // in milliseconds
GetMinEmptyBlockGap() int64 // in milliseconds
GetValidityWindow() int64 // in milliseconds
GetMaxActionsPerTx() uint8
GetMaxOutputsPerAction() uint8
GetMinUnitPrice() fees.Dimensions
GetUnitPriceChangeDenominator() fees.Dimensions
GetWindowTargetUnits() fees.Dimensions
GetMaxBlockUnits() fees.Dimensions
GetFeeMarketPriceChangeDenominator() uint64
GetFeeMarketWindowTargetUnits() uint64
GetFeeMarketMinUnitPrice() uint64
GetBaseComputeUnits() uint64
// Invariants:
// * Controllers must manage the max key length and max value length (max network
// limit is ~2MB)
// * Creating a new key involves first allocating and then writing
// * Keys are only charged once per transaction (even if used multiple times), it is
// up to the controller to ensure multiple usage has some compute cost
GetSponsorStateKeysMaxChunks() []uint16
GetStorageKeyReadUnits() uint64
GetStorageValueReadUnits() uint64 // per chunk
GetStorageKeyAllocateUnits() uint64
GetStorageValueAllocateUnits() uint64 // per chunk
GetStorageKeyWriteUnits() uint64
GetStorageValueWriteUnits() uint64 // per chunk
FetchCustom(string) (any, bool)
}Rules govern block validity and are requested from the Controller prior to
executing any block. The hypersdk performs this request so that the
Controller can modify any Rules on-the-fly. Many common rules are provided
directly in the interface but there is also an option to provide custom rules
that can be accessed during Auth or Action execution.
You can view what this looks like in the indexvm by clicking
here. In the
case of the indexvm, the custom rule support is used to set the cost for
adding anything to state (which is a very hypervm-specific value).
You can view what the import Action associated with the above examples looks like
here
As mentioned above, it is up to the hypervm to implement a message format
that it can understand (so that it can parse inbound AWM messages). In the
future, we expect that there will be common message definitions that will be
compatible with most hypervms (and maintained in the hypersdk).
This is a collection of posts from the community about the hypersdk and how to use it in your own hypervm.
- Introducing HyperSDK
- HyperSDK - Chorus One
- Building blockchains in days w/ HyperSDK
- An Analysis of the Developing State of Avalanche’s Technology
- Avalanche VMs deep-dive #1: HyperSDK/tokenvm
- Avalanche – Building High Performance VMs With HyperSDK
- Avalanche’s HyperSDK blockchain upgrade hits 143K TPS on testnet
- Avalanche’s HyperSDK
This is a collection of community projects building on top of the hypersdk.
- NodeKit: Decentralizing The L2 Sequencer on a Subnet
- OracleVM: Providing OffChain Data to the Avalanche Ecosystem
If you want to take the lead on any of these items, please start a discussion or reach out on the Avalanche Discord.
- Add support for Fixed-Fee Accounts (pay set unit price no matter what)
- Use a memory arena (pre-allocated memory) to avoid needing to dynamically allocate memory during block and transaction parsing
- Add a module that does Data Availability sampling on top of the networking interface exposed by AvalancheGo (only store hashes in blocks but leave VM to fetch pieces as needed on its own)
- Implement support for S3 and PostgreSQL storage backends
- Provide optional auto-serialization/deserialization of
ActionsandAuthif only certain types are used in their definition - Add a module that could be used to track the location of various pieces
of data across a network (see consistent
hasher)
of
hypervmparticipants (even better if this is made abstract to any implementer such that they can just register and request data from it and it is automatically handled by the network layer). This module should make it possible for an operator to use a single backend (like S3) to power storage for multiple hosts. - Only set
export CGO_CFLAGS="-O -D__BLST_PORTABLE__"when running on MacOS/Windows (will make Linux much more performant)
If you get the following error, make sure to install gcc before running
./scripts/build.sh:
# github.com/supranational/blst/bindings/go
../../../go/pkg/mod/github.com/supranational/[email protected]/bindings/go/rb_tree.go:130:18: undefined: Message