A customizable hardware prefetching framework using online reinforcement learning as described in the MICRO 2021 paper by Bera et al. (https://arxiv.org/pdf/2109.12021.pdf).

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

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).

MegIS is the first in-storage processing system designed to significantly reduce the data movement overhead of the end-to-end metagenomic analysis pipeline. Described in the ISCA 2024 paper by Mansouri Ghiasi et al.: https://arxiv.org/pdf/2406.19113

BreakHammer is a technique that reduces the performance overhead of RowHammer mitigation mechanisms by carefully reducing the number of performed RowHammer-preventive actions without compromising system robustness. Described in the MICRO 2024 paper: https://arxiv.org/abs/2404.13477.

PyGim is the first runtime framework to efficiently execute Graph Neural Networks (GNNs) on real Processing-in-Memory systems. It provides a high-level Python interface, currently integrated with PyTorch, and supports various GNN models and real-world input graphs. Described by SIGMETRICS'25 by Giannoula et al. (https://arxiv.org/pdf/2402.16731)

Source code & scripts for distributed machine learning training workloads on a real-world Processing-In-Memory system (i.e., UPMEM). Described in our PACT'24 paper by Rhyner et al. at https://arxiv.org/pdf/2404.07164v2

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)

Genome-on-Diet is a fast and memory-frugal framework for exemplifying sparsified genomics for read mapping, containment search, and metagenomic profiling. It is much faster & more memory-efficient than minimap2 for Illumina, HiFi, and ONT reads. Described by Alser et al. (preliminary version: https://arxiv.org/abs/2211.08157).

DRAM Bender is the first open source DRAM testing infrastructure that can be used to easily and comprehensively test state-of-the-art HBM2 chips and DDR4 modules of different form factors. Six prototypes are available on different FPGA boards. Described in our preprint: https://arxiv.org/pdf/2211.05838.pdf