# bitcoinsecp256k1-bench crate description

This crate is part of the Bitcoin system and is
a Rust translation of the C++ Bitcoin Core. It
provides benchmarking tools for various secp256k1
functions.

Notice: "This crate is part of a direct
translation from C++ to Rust of the Bitcoin
Core. As such, some of the function bodies may
still be in the process of translation. Please
note that this system will become testable once
the translation process is complete."

Below are listed the tokens from this crate, and
a brief description of their purpose:

- BenchEcdhData: A structure representing data
  used in benchmarking ECDH.

- bench_ecdh: Benchmark ECDH.

- bench_ecdh_setup: Prepare for ECDH benchmark.

- secp256k1_bench_ecdh_main: Main function for
  ECDH benchmark.

- BenchSignData: A structure representing data
  used in benchmarking signing.

- bench_sign_run: Run signing benchmark.

- bench_sign_setup: Prepare for signing benchmark.

- secp256k1_bench_sign_main: Main function for
  signing benchmark.

- BenchVerifyData: A structure representing data
  used in benchmarking signature verification.

- bench_verify: Benchmark signature verification.

- bench_verify_openssl: Benchmark signature
  verification using OpenSSL.

- secp256k1_bench_verify_main: Main function for
  signature verification benchmark.

- BenchData: A structure representing data used in
  various benchmarks.

- bench_ecmult_1: Benchmark constant-time scalar
  multiplication.

- bench_ecmult_1_teardown: Cleanup after
  constant-time scalar multiplication benchmark.

- bench_ecmult_1g: Benchmark constant-time
  multiplication by the generator.

- bench_ecmult_1g_teardown: Cleanup after
  constant-time multiplication by the generator
  benchmark.

- bench_ecmult_2g: Benchmark constant-time
  multiplication by 2 times the generator.

- bench_ecmult_2g_teardown: Cleanup after
  constant-time multiplication by 2 times the
  generator benchmark.

- bench_ecmult_const: Benchmark variable-time
  scalar multiplication.

- bench_ecmult_const_teardown: Cleanup after
  variable-time scalar multiplication benchmark.

- bench_ecmult_gen: Benchmark multiplication by
  the generator.

- bench_ecmult_gen_teardown: Cleanup after
  multiplication by the generator benchmark.

- bench_ecmult_multi: Benchmark multiple scalar
  multiplication.

- bench_ecmult_multi_callback: Helper function for
  benchmarking multiple scalar multiplication.

- bench_ecmult_multi_setup: Prepare for multiple
  scalar multiplication benchmark.

- bench_ecmult_multi_teardown: Cleanup after
  multiple scalar multiplication benchmark.

- bench_ecmult_setup: Prepare for scalar
  multiplication benchmark.

- bench_ecmult_teardown_helper: Cleanup after
  scalar multiplication benchmark.

- generate_scalar: Generate a random scalar.

- hash_into_offset: Convert a hash into an offset.

- help: Display help message.

- run_ecmult_bench: Run scalar multiplication
  benchmarks.

- run_ecmult_multi_bench: Run multiple scalar
  multiplication benchmarks.

- secp256k1_bench_ecmult_main: Main function for
  scalar multiplication benchmarks.

- BenchInv: Benchmark inversion.

- bench_context_sign: Benchmark
  secp256k1_context_create_signing() function.

- bench_context_verify: Benchmark
  secp256k1_context_create_verify() function.

- bench_ecmult_wnaf: Benchmark w-NAF constant-time
  scalar multiplication.

- bench_field_inverse: Benchmark inversion in
  a field element.

- bench_field_inverse_var: Benchmark variable-time
  inversion in a field element.

- bench_field_mul: Benchmark multiplication of two
  field elements.

- bench_field_normalize: Benchmark normalization
  of a field element.

- bench_field_normalize_weak: Benchmark weak
  normalization of a field element.

- bench_field_sqr: Benchmark squaring of a field
  element.

- bench_field_sqrt: Benchmark square root of
  a field

125> how do we benchmark ecdh? what are some
techniques?

In general, benchmarking ecdh involves measuring
the time it takes to perform a large number of key
exchanges between two parties. The goal is to
evaluate the performance of the implementation of
the ecdh algorithm under different conditions,
such as different key sizes, different message
sizes, and different hardware configurations.

One common technique for benchmarking ecdh is to
use a fixed set of parameters, such as a fixed key
size and a fixed message size, and measure the
time it takes to perform a fixed number of key
exchanges. This allows for a comparison of
different implementations under the same
conditions.

Another technique is to vary the key size or the
message size and measure the time it takes to
perform a single key exchange. This allows for an
evaluation of the performance of the
implementation as the size of the inputs change.

In addition to measuring the time it takes to
perform key exchanges, other metrics can be used
to evaluate the performance of ecdh, such as
memory usage and code size.

It is important to carefully select the benchmarks
used to evaluate ecdh, as different benchmarks can
produce different results and may not accurately
reflect the performance of the implementation in
a real-world scenario.

126> are there other techniques?

Yes, there are other techniques for benchmarking
ECDH. One common technique is to use
a pre-computed table of points, known as
a precomputed table. This table can be used to
speed up the scalar multiplication operation by
a significant amount. Another technique is to use
a cache to store the intermediate values of the
scalar multiplication operation, which can also
improve performance. Additionally, optimizing the
implementation of the underlying elliptic curve
arithmetic can also lead to performance gains.