zhaojer/compiler_hot_paths

Dataset Card for Compiler Hot Paths

Dataset Description

This dataset consists of 1561 compiler paths generated from 26 C programs in the Polybench Benchmark Suite using the Ball-Larus Algorithm. Each path, a sequence of LLVM IR instructions, is has three associated values:

1. count, an integer indicating the number of times this path is executed in the original program.
2. source_file, a string indicating which program was this path from.
3. label, an integer of 0 or 1 indicating whether this path is "cold" or "hot" respectively.

Note: 4 programs (deriche, cholesky, gramschmidt, correlation) were excluded because we encountered errors when running them.

Uses

This dataset was used to train/fine-tune machine learning models to perform hot path predictions: Given a path, predict whether it is "hot" or "cold". A path is considered "hot" if it is executed more than a threshold of n times, where we defined n = 1, otherwise it is considered "cold".

Dataset Structure

The dataset is split into train (1190, 75%), validation (211, 15%), and test (160, 10%) sets. The test set consists of paths from 4 programs (in PolyBench), namely, jacobi-2d, syr2k, durbin, 2mm. These 4 programs were randomly selected to be the test set before generating the paths. This guarantees that the models have never seen the test set's programs. The train and validation sets consist of the remaining 22 programs, which were randomly split after generating the paths (while maintaining the hot-to-cold-paths ratio), meaning that some paths in the validation set and training set may come from the same C program. However, this likely won't be an issue since the paths themselves are distinct.