SAFARI Research Group at ETH Zurich and Carnegie Mellon University (CMU-SAFARI)

SAFARI Research Group at ETH Zurich and Carnegie Mellon University

CMU-SAFARI

Geek Repo

Site for source code and tools distribution from SAFARI Research Group at ETH Zurich and Carnegie Mellon University.

Location:ETH Zurich and Carnegie Mellon University

Home Page:https://safari.ethz.ch/

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SAFARI Research Group at ETH Zurich and Carnegie Mellon University's repositories

ramulator

A Fast and Extensible DRAM Simulator, with built-in support for modeling many different DRAM technologies including DDRx, LPDDRx, GDDRx, WIOx, HBMx, and various academic proposals. Described in the IEEE CAL 2015 paper by Kim et al. at http://users.ece.cmu.edu/~omutlu/pub/ramulator_dram_simulator-ieee-cal15.pdf

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MQSim

MQSim is a fast and accurate simulator modeling the performance of modern multi-queue (MQ) SSDs as well as traditional SATA based SSDs. MQSim faithfully models new high-bandwidth protocol implementations, steady-state SSD conditions, and the full end-to-end latency of requests in modern SSDs. It is described in detail in the FAST 2018 paper by Arash Tavakkol et al., "MQSim: A Framework for Enabling Realistic Studies of Modern Multi-Queue SSD Devices" (https://people.inf.ethz.ch/omutlu/pub/MQSim-SSD-simulation-framework_fast18.pdf)

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ramulator2

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

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SoftMC

SoftMC is an experimental FPGA-based memory controller design that can be used to develop tests for DDR3 SODIMMs using a C++ based API. The design, the interface, and its capabilities and limitations are discussed in our HPCA 2017 paper: "SoftMC: A Flexible and Practical Open-Source Infrastructure for Enabling Experimental DRAM Studies" <https://people.inf.ethz.ch/omutlu/pub/softMC_hpca17.pdf>

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Pythia

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).

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DAMOV

DAMOV is a benchmark suite and a methodical framework targeting the study of data movement bottlenecks in modern applications. It is intended to study new architectures, such as near-data processing. Described by Oliveira et al. (preliminary version at https://arxiv.org/pdf/2105.03725.pdf)

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Hermes

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)

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PiDRAM

PiDRAM is the first flexible end-to-end framework that enables system integration studies and evaluation of real Processing-using-Memory techniques. Prototype on a RISC-V rocket chip system implemented on an FPGA. Described in our paper: https://arxiv.org/abs/2111.00082

Scrooge

Scrooge is a high-performance pairwise sequence aligner based on the GenASM algorithm. Scrooge includes three novel algorithmic improvements on top of GenASM, and high-performance CPU and GPU implementations. Described by Lindegger et al. at https://doi.org/10.48550/arXiv.2208.09985

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BLEND

BLEND is a mechanism that can efficiently find fuzzy seed matches between sequences to significantly improve the performance and accuracy while reducing the memory space usage of two important applications: 1) finding overlapping reads and 2) read mapping. Described by Firtina et al. (published in NARGAB https://doi.org/10.1093/nargab/lqad004)

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DRAM-Bender

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

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RawHash

RawHash is the first mechanism that can accurately and efficiently map raw nanopore signals to large reference genomes (e.g., a human reference genome) in real-time without using powerful computational resources (e.g., GPUs). Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440)

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RowPress

Source code & scripts for experimental characterization and real-system demonstration of RowPress, a widespread read disturbance phenomenon in DRAM that is different from RowHammer. Described in our ISCA'23 paper by Luo et al. at https://people.inf.ethz.ch/omutlu/pub/RowPress_isca23.pdf

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Victima

Victima is a new software-transparent technique that greatly extends the address translation reach of modern processors by leveraging the underutilized resources of the cache hierarchy, as desribed in the MICRO 2023 paper by Kanellopoulos et al. (https://arxiv.org/pdf/2310.04158/)

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SPARTA

A novel spatial accelerator for horizontal diffusion weather stencil computation, as described in ICS 2023 paper by Singh et al. (https://arxiv.org/pdf/2303.03509.pdf)

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SimplePIM

SimplePIM is the first high-level programming framework for real-world processing-in-memory (PIM) architectures. Described in the PACT 2023 paper by Chen et al. (https://arxiv.org/pdf/2310.01893.pdf).

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Genome-on-Diet

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).

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NATSA

NATSA is the first near-data-processing accelerator for time series analysis based on the Matrix Profile (SCRIMP) algorithm. NATSA exploits modern 3D-stacked High Bandwidth Memory (HBM) to enable efficient and fast matrix profile computation near memory. Described in ICCD 2020 by Fernandez et al. https://people.inf.ethz.ch/omutlu/pub/NATSA_time-series-analysis-near-data_iccd20.pdf

ABACuS

New RowHammer mitigation mechanism that is area-, performance-, and energy-efficient especially at very low (e.g., 125) RowHammer thresholds, as described in the USENIX Security'24 paper https://arxiv.org/pdf/2310.09977.pdf

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EINSim

DRAM error-correction code (ECC) simulator incorporating statistical error properties and DRAM design characteristics for inferring pre-correction error characteristics using only the post-correction errors. Described in the 2019 DSN paper by Patel et al.: https://people.inf.ethz.ch/omutlu/pub/understanding-and-modeling-in-DRAM-ECC_dsn19.pdf.

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Virtuoso

Virtuoso is a new simulator that focuses on modelling various memory management and virtual memory aspects.

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CoMeT

CoMeT is a new low-cost RowHammer mitigation that uses Count-Min Sketch-based aggressor row tracking

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GateSeeder

GateSeeder is the first near-memory CPU-FPGA co-design for alleviating both the compute-bound and memory-bound bottlenecks in short and long-read mapping. GateSeeder outperforms Minimap2 by up to 40.3×, 4.8×, and 2.3× when mapping real ONT, HiFi, and Illumina reads, respectively.

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RawAlign

RawAlign is a real-time raw nanopore read mapper based on the Seed-Filter-Align paradigm as described by Lindegger et al. (https://arxiv.org/abs/2310.05037)

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SelfManagingDRAM

Source code for evaluating the performance and DRAM energy benefits of Self-Managing DRAM (SMD), proposed in https://arxiv.org/abs/2207.13358

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sasiml

An extensible and fully programable cycle-accurate Spatial Architecture simulator for Machine Learning Workloads. Described in detail in the IEEE TC 2023 paper by Orosa et al. at https://arxiv.org/abs/2202.02310

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Utopia

Utopia is a new hybrid address mapping scheme that accelerates address translation while supporting all conventional VM features as described by Kanellopoulos et al. (https://arxiv.org/abs/2211.12205)

alignment-in-memory

AIM (Alignment-in-Memory), A Framework for High-throughput Sequence Alignment using Real Processing-in-Memory Systems, Bioinformatics, btad155, https://doi.org/10.1093/bioinformatics/btad155

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MetaTrinity

MetaTrinity is a novel metagenomic analysis tool employing efficient containment search techniques and heuristics for read mapping to achieve significant speedup while maintaining high accuracy. This positions MetaTrinity as an efficient solution, optimally balancing speed and precision in metagenomic analysis.

SequenceLab

SequenceLab is a benchmark suite for evaluating computational methods for comparing genomic sequences, such as pre-alignment filters and pairwise sequence alignment algorithms. SequenceLab is described by Rumpf et al. at https://arxiv.org/abs/2310.16908

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