Features

Logging, debugging and proving options

Logging

Pico leverages Rust’s standard logging utilities to provide detailed runtime information, particularly about performance and program statistics. You can control the verbosity of the logs via the RUST_LOG environment variable:

• Info Level: Set RUST_LOG=info to output overall performance data and high-level progress information.

• Debug Level: Set RUST_LOG=debug to display detailed logs, including statistics of chunks and records as they are generated and processed.

For scenarios where you want to save logs to a file without color codes (which may be embedded by default), you can pipe the output through a tool like ansi2txt. This conversion ensures that the log file remains clean and free of terminal-specific formatting, as the tracing framework does not automatically adjust colors based on environment variables.

Debugging

In the rare event that proving fails on a correctly executing binary, Pico provides additional debug capabilities to assist in pinpointing issues:

• Enhanced Debugging Features: Enable the debug and debug-lookups features when running the prover. These features provide extra context by outputting detailed information on individual constraints and lookup operations within each processing batch.

• Minimal Memory Impact: Since debug information is generated from data already in memory for the current batch of proofs, enabling debugging does not incur a significant additional memory cost. The debug data can be discarded once the batch is processed and debugged.

• Accessing Debug Data: Combine the debugging features with RUST_LOG=debug to capture detailed logs.

Proving Options

Pico offers several configurable parameters to optimize the proving process for your system’s resources and performance requirements:

• Automatic Configuration: By default, Pico automatically adjusts standard options, such as chunk and batch sizes, according to the available memory on the running machine.

• Manual Overrides: Developers can fine-tune the proving process by setting the following environment variables:

  • CHUNK_SIZE: Determines the number of cycles executed before splitting records. This helps manage the trace size, and setting this value to a power of 2 is recommended.

  • CHUNK_BATCH_SIZE: Specifies the number of chunks processed concurrently. Set this value based on the total available system memory and the per-record/trace memory cost, ensuring you do not exceed your system’s capacity.

These options allow you to balance performance and resource utilization, making it possible to optimize Pico for a wide range of environments—from resource-constrained setups to high-performance systems.

Features

pico-vm comes enabled with several features by default. These being strict, rayon, and nightly-features. strict is a compile time option for #![deny(warnings)] on the entire pico-vm module. rayon enables the usage of rayon's ParallelIterator and related traits to use multithreading to speed up the proving process. This feature should be left on unless you wish to compile a single threaded prover for profiling reasons, as rayon tends to pollute the stack trace when running flamegraph. nightly-features enables certain CPU-specific performance enhancements, enabling further optimizations with -march=native and turning on AVX2 by default on x86-based architectures. AVX512 can be enabled via additional RUSTFLAGS as well. This should be left on, like rayon, unless you have a specific reason not to.

To build pico-vm without default features, simply set default-features = false in your Cargo.toml or run cargo build -p pico-vm --no-default-features for your local build environment, maybe adding --example if you want to build a specific example in addition to the Rust library.

Single threaded profiling

As mentioned in the previous section, we support single threaded builds in order to generate neater flamegraphs for profiling purposes. For example, to build test_riscv for profiling, run

cargo build -p pico-vm --no-default-features --profile --profiling --example test_riscv

to build the binary and then run

sudo flamegraph -o flamegraph.svg -- ./target/profiling/examples/test_riscv

with cargo flamegraph to produce a flamegraph that you can use to explore cost centers.