SAFARI Research Group at ETH Zurich and Carnegie Mellon University
- 833 followers
- ETH Zurich and Carnegie Mellon University
- https://safari.ethz.ch/
- omutlu@gmail.com
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Repositories
- Hermes Public
A speculative mechanism to accelerate long-latency off-chip load requests by removing on-chip cache access latency from their critical path, as described by MICRO 2022 paper by Bera et al. (https://arxiv.org/pdf/2209.00188.pdf)
CMU-SAFARI/Hermes’s past year of commit activity - Virtuoso Public
Virtuoso is a fast, accurate and versatile simulation framework designed for virtual memory research. Virtuoso uses a new simulation methodology for estimating OS overheads and models diverse VM designs, incorporating state-of-the-art TLB techniques, page table structures etc. More details in our ASPLOS 2025 paper: https://arxiv.org/pdf/2403.04635
CMU-SAFARI/Virtuoso’s past year of commit activity - RawBench Public
A comprehensive benchmarking framework for raw nanopore signal analysis, as described by Eris et al. (https://arxiv.org/pdf/2510.03629)
CMU-SAFARI/RawBench’s past year of commit activity - ramulator2 Public
Ramulator 2.0 is a modern, modular, extensible, and fast cycle-accurate DRAM simulator. It provides support for agile implementation and evaluation of new memory system designs (e.g., new DRAM standards, emerging RowHammer mitigation techniques). Described in our paper https://people.inf.ethz.ch/omutlu/pub/Ramulator2_arxiv23.pdf
CMU-SAFARI/ramulator2’s past year of commit activity - Athena Public
A reinforcement learning based policy to dynamically coordinate off-chip predictor with multiple data prefetchers, as described in the HPCA2026 paper by Bera and Lang et al.: https://arxiv.org/abs/2601.17615
CMU-SAFARI/Athena’s past year of commit activity - CoMeT Public
CoMeT is a new low-cost RowHammer mitigation that uses Count-Min Sketch-based aggressor row tracking, as described in our HPCA'24 paper https://arxiv.org/pdf/2402.18769.pdf
CMU-SAFARI/CoMeT’s past year of commit activity - RawHash Public
RawHash can accurately and efficiently map raw nanopore signals to reference genomes of varying sizes (e.g., from viral to a human genomes) in real-time without basecalling. Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440).
CMU-SAFARI/RawHash’s past year of commit activity