## Module pezframe_benchmarking_weight

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Expand description

Learn about benchmarking and weight.

## §FRAME Benchmarking and Weights.

This reference doc explores the concept of weights within Pezkuwi-SDK runtimes, and more specifically how FRAME-based runtimes handle it.

### §Metering

The existence of “weight” as a concept in Pezkuwi-SDK is a direct consequence of the usage of WASM as a virtual machine. Unlike a metered virtual machine like EVM, where every instruction can have a (fairly) deterministic “cost” (also known as “gas price”) associated with it, WASM is a stack machine with more complex instruction set, and more unpredictable execution times. This means that unlike EVM, it is not possible to implement a “metering” system in WASM. A metering system is one in which instructions are executed one by one, and the cost/gas is stored in an accumulator. The execution may then halt once a gas limit is reached.

In Pezkuwi-SDK, the WASM runtime is not assumed to be metered.

### §Trusted Code

Another important difference is that EVM is mostly used to express smart contracts, which are foreign and untrusted codes from the perspective of the blockchain executing them. In such cases, metering is crucial, in order to ensure a malicious code cannot consume more gas than expected.

This assumption does not hold about the runtime of Pezkuwi-SDK-based blockchains. The runtime is trusted code, and it is assumed to be written by the same team/developers who are running the blockchain itself. Therefore, this assumption of “untrusted foreign code” does not hold.

This is why the runtime can opt for a more performant, more flexible virtual machine like WASM, and get away without having metering.

### §Benchmarking

With the matter of untrusted code execution out of the way, the need for strict metering goes out of the way. Yet, it would still be very beneficial for block producers to be able to know an upper bound on how much resources a operation is going to consume before actually executing that operation. This is why FRAME has a toolkit for benchmarking pallets: So that this upper bound can be empirically determined.

> Note: Benchmarking is a static analysis: It is all about knowing the upper bound of how much resources an operation takes statically, without actually executing it. In the context of FRAME extrinsics, this static-ness is expressed by the keyword “pre-dispatch”.

To understand why this upper bound is needed, consider the following: A block producer knows they have 20ms left to finish producing their block, and wishes to include more transactions in the block. Yet, in a metered environment, it would not know which transaction is likely to fit the 20ms. In a benchmarked environment, it can examine the transactions for their upper bound, and include the ones that are known to fit based on the worst case.

The benchmarking code can be written as a part of FRAME pezpallet, using the macros provided in [`pezframe_benchmarking`]. See any of the existing pallets in `pezkuwi-sdk`, or the pallets in our `crate::pezkuwi_sdk::templates` for examples.

### §Weight

Finally, [`pezsp_weights::Weight`] is the output of the benchmarking process. It is a two-dimensional data structure that demonstrates the resources consumed by a given block of code (for example, a transaction). The two dimensions are:

- reference time: The time consumed in pico-seconds, on a reference hardware.
- proof size: The amount of storage proof necessary to re-execute the block of code. This is mainly needed for teyrchain <> relay-chain verification.

### §How To Write Benchmarks: Worst Case

The most important detail about writing benchmarking code is that it must be written such that it captures the worst case execution of any block of code.

Consider:

ⓘ

    #[pezpallet::weight(10_000)]
    pub fn simple_transfer(
    	origin: OriginFor<T>,
    	destination: T::AccountId,
    	amount: u32,
    ) -> DispatchResult {
    	let destination_exists = todo!();
    	if destination_exists {
    		// simpler code path
    	} else {
    		// more complex code path
    	}
    	Ok(())
    }

If this block of code is to be benchmarked, then the benchmarking code must be written such that it captures the worst case.

### §Gluing Pezpallet Benchmarking with Runtime

FRAME pallets are mandated to provide their own benchmarking code. Runtimes contain the boilerplate needed to run these benchmarking (see Running Benchmarks below). The outcome of running these benchmarks are meant to be fed back into the pezpallet via a conventional `trait WeightInfo` on `Config`:

ⓘ

    pub trait WeightInfo {
    	fn simple_transfer() -> Weight;
    }

Then, individual functions of this trait are the final values that we assigned to the [`pezframe::pezpallet_macros::weight`] attribute:

ⓘ

    #[pezpallet::weight(T::WeightInfo::simple_transfer())]
    pub fn simple_transfer_2(
    	origin: OriginFor<T>,
    	destination: T::AccountId,
    	amount: u32,
    ) -> DispatchResult {
    	let destination_exists = todo!();
    	if destination_exists {
    		// simpler code path
    	} else {
    		// more complex code path
    	}
    	Ok(())
    }

### §Manual Refund

Back to the assumption of writing benchmarks for worst case: Sometimes, the pre-dispatch weight significantly differ from the post-dispatch actual weight consumed. This can be expressed with the following FRAME syntax:

ⓘ

    #[pezpallet::weight(T::WeightInfo::simple_transfer())]
    pub fn simple_transfer_3(
    	origin: OriginFor<T>,
    	destination: T::AccountId,
    	amount: u32,
    ) -> DispatchResultWithPostInfo {
    	// ^^ Notice the new return type
    	let destination_exists = todo!();
    	if destination_exists {
    		// simpler code path
    		// Note that need for .into(), to convert `()` to `PostDispatchInfo`
    		// See: https://docs.pezkuwichain.io/sdk/master/pezframe_support/dispatch/struct.PostDispatchInfo.html#impl-From%3C()%3E-for-PostDispatchInfo
    		Ok(().into())
    	} else {
    		// more complex code path
    		let actual_weight =
    			todo!("this can likely come from another benchmark that is NOT the worst case");
    		let pays_fee = todo!("You can set this to `Pays::Yes` or `Pays::No` to change if this transaction should pay fees");
    		Ok(pezframe::deps::pezframe_support::dispatch::PostDispatchInfo {
    			actual_weight: Some(actual_weight),
    			pays_fee,
    		})
    	}
    }

### §Running Benchmarks

Two ways exist to run the benchmarks of a runtime.

1. The old school way: Most Pezkuwi-SDK based nodes (such as the ones integrated in `templates`) have a `benchmark` subcommand integrated into themselves.
2. The more `crate::reference_docs::omni_node` compatible way of running the benchmarks would be using `frame-omni-bencher` CLI, which only relies on a runtime.

Note that by convention, the runtime and pallets always have their benchmarking code feature gated as behind `runtime-benchmarks`. So, the runtime should be compiled with `--features runtime-benchmarks`.

### §Automatic Refund of `proof_size`.

A new feature in FRAME allows the runtime to be configured for “automatic refund” of the proof size weight. This is very useful for maximizing the throughput of teyrchains. Please see: `crate::guides::enable_pov_reclaim`.

### §Summary

Pezkuwi-SDK runtimes use a more performant VM, namely WASM, which does not have metering. In return they have to be benchmarked to provide an upper bound on the resources they consume. This upper bound is represented as [`pezsp_weights::Weight`].

### §Future: PolkaVM

With the transition of Pezkuwi relay chain to JAM, a set of new features are being introduced, one of which being a new virtual machine named PolkaVM that is as flexible as WASM, but also capable of metering. This might alter the future of benchmarking in FRAME and Pezkuwi-SDK, rendering them not needed anymore once PolkaVM is fully integrated into Pezkuwi-sdk. For a basic explanation of JAM and PolkaVM, see here.

## Modules§

pezpallet
  The `pezpallet` module in each FRAME pezpallet hosts the most important items needed to construct this pezpallet.