datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
AIDE-Chip-15K-gem5-Sims
AIDE-Chip 15K gem5 Simulation Dataset
AIDE-Chip-15K-gem5-Sims is a structured dataset of approximately 15,000 validated RISC-V gem5 simulations covering cache hierarchy design-space exploration (DSE) for single-core processors.
The dataset was generated using gem5's Syscall Emulation (SE) mode and six representative workloads, spanning compute-bound, memory-bound, and irregular access patterns. Each sample maps cache configuration parameters to IPC and L2 miss rate, enabling… See the full description on the dataset page: https://huggingface.co/datasets/uralstech/AIDE-Chip-15K-gem5-Sims.pie-gem5-pairs
PIE gem5-timed code optimization (src,tgt pairs)
C++ program-optimization data derived from the PIE dataset
("Learning Performance-Improving Code Edits"),
re-timed end-to-end with gem5 (x86 Skylake, syscall-emulation mode) at
per-test-case granularity. One row per official (source, target) program pair.
This dataset is reward-agnostic: it ships the full per-test-case reference timings and
case manifests so a downstream RL / eval pipeline decides at runtime how many cases to use… See the full description on the dataset page: https://huggingface.co/datasets/stablegradients/pie-gem5-pairs.pie-gem5-bysrc
PIE gem5-timed code optimization (per source program)
C++ program-optimization data derived from the PIE dataset
("Learning Performance-Improving Code Edits"),
re-timed end-to-end with gem5 (x86 Skylake, syscall-emulation mode) at
per-test-case granularity. One row per unique (problem, source) program; the best surviving target is kept as an oracle ceiling.
This dataset is reward-agnostic: it ships the full per-test-case reference timings and
case manifests so a downstream RL /… See the full description on the dataset page: https://huggingface.co/datasets/stablegradients/pie-gem5-bysrc.