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Name: SAFARI Research Group at ETH Zurich and Carnegie Mellon University

Type: Organization

Bio: 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

Blog: https://safari.ethz.ch/

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

abacus icon 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

airlift icon airlift

AirLift is a tool that updates mapped reads from one reference genome to another. Unlike existing tools, It accounts for regions not shared between the two reference genomes and enables remapping across all parts of the references. Described by Kim et al. (preliminary version at http://arxiv.org/abs/1912.08735)

alignment-in-memory icon 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

aphmm-gpu icon aphmm-gpu

ApHMM-GPU is the first GPU implementation of the Baum-Welch algorithm for profile Hidden Markov Models (pHMMs). It includes many of the software optimizations as proposed in the ApHMM paper, which is described by Firtina et al. (preliminary version at https://arxiv.org/abs/2207.09765).

apollo icon apollo

Apollo is an assembly polishing algorithm that attempts to correct the errors in an assembly. It can take multiple set of reads in a single run and polish the assemblies of genomes of any size. Described in the Bioinformatics journal paper (2020) by Firtina et al. at https://people.inf.ethz.ch/omutlu/pub/apollo-technology-independent-genome-assembly-polishing_bioinformatics20.pdf

asmsim icon asmsim

This simulator models multi core systems with primary focus on the memory hierarchy. It models a trace-based out-of-order core frontend and memory scheduling policies like FRFCFS, ATLAS, TCM and slowdown estimation models, ASM and MISE. Based on the MICRO 2015 paper at https://users.ece.cmu.edu/~omutlu/pub/application-slowdown-model_micro15.pdf

bdicompression icon bdicompression

Source code for the Base-Delta-Immediate Compression Algorithm (described in the PACT 2012 paper by Pekhimenko et al. at http://users.ece.cmu.edu/~omutlu/pub/bdi-compression_pact12.pdf)

beer icon beer

BEER determines an ECC code's parity-check matrix based on the uncorrectable errors it can cause. BEER targets Hamming codes that are used for DRAM on-die ECC but can be extended to apply to other linear block codes (e.g., BCH, Reed-Solomon). BEER is described in the 2020 MICRO paper by Patel et al.: https://arxiv.org/abs/2009.07985.

biodynamo icon biodynamo

BioDynamo is a flexible and high-performance agent based simulation engine. This repository contains artifacts and materials to support the reproducibility of the paper: Breitwieser et al., "High-Performance and Scalable Agent-Based Simulation with BioDynaMo," accepted to PPoPP '23: https://arxiv.org/pdf/2301.06984.pdf

blend icon 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)

blockhammer icon blockhammer

Source code for the cycle-level simulator and RTL implementation of BlockHammer proposed in our HPCA 2021 paper: Yaglikci et. al., "BlockHammer: Preventing RowHammer at Low Cost by Blacklisting Rapidly-Accessed DRAM Rows" at https://people.inf.ethz.ch/omutlu/pub/BlockHammer_preventing-DRAM-rowhammer-at-low-cost_hpca21.pdf

cache-memory-hog icon cache-memory-hog

Cache and main memory hog programs. These are programs with specific access patterns to evict the already existing cache blocks of various applications. These programs were designed to demonstrate that application performance is nearly linearly correlated with cache access rate (as shown in Section 3.1 of Subramanian et al. "The Application Slowdown Model" @ https://users.ece.cmu.edu/~omutlu/pub/application-slowdown-model_micro15.pdf)

clrdram icon clrdram

Circuit-level model for the Capacity-Latency Reconfigurable DRAM (CLR-DRAM) architecture. This repository contains the SPICE models of the CLR-DRAM architecture and the baseline architecture used in our ISCA 2020 paper "Luo et al., CLR-DRAM: A Low-Cost DRAM Architecture Enabling Dynamic Capacity-Latency Trade-Off": https://people.inf.ethz.ch/omutlu/pub/CLR-DRAM_capacity-latency-reconfigurable-DRAM_isca20.pdf

comet icon comet

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

covidhunter icon covidhunter

COVIDHunter 🦠:construction:: An accurate and flexible COVID-19 outbreak simulation model that forecasts the strength of future mitigation measures and the numbers of cases, hospitalizations, and deaths for a given day, while considering the potential effect of environmental conditions. Described by Alser et al. (preliminary version at https://arxiv.org/abs/2102.03667 and https://doi.org/10.1101/2021.02.06.21251265).

crow icon crow

Source code for the architectural and circuit-level simulators used for modeling the CROW (Copy-ROW DRAM) mechanism proposed in our ISCA 2019 paper "CROW: A Low-Cost Substrate for Improving DRAM Performance, Energy Efficiency, and Reliability". Paper is at: https://people.inf.ethz.ch/omutlu/pub/CROW-DRAM-substrate-for-performance-energy-reliability_isca19.pdf.

damov icon 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)

diva-dram icon diva-dram

This repository provides characterization data collected over 96 DDR3 SO-DIMMs, related to the following paper: Lee et al., "Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms", SIGMETRICS 2017. https://people.inf.ethz.ch/omutlu/pub/DIVA-low-latency-DRAM_sigmetrics17-paper.pdf

dram-bender icon 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

dram-datasheet-survey icon dram-datasheet-survey

A survey of manufacturer-provided DRAM operating parameters and timings as specified by DRAM chip datasheets from between 1970 and 2021. This data and its analysis are described in the 2022 paper by Patel et al.: https://arxiv.org/abs/2204.10378

dram-latency-variation-study icon dram-latency-variation-study

Latency characterization data collected from 30 real DRAM SO-DIMMs. You can find the background and analysis on the data in our SIGMETRICS'16 paper "Understanding Latency Variation in Modern DRAM Chips: Experimental Characterization, Analysis, and Optimization".

dram-voltage-study icon dram-voltage-study

Experimental study and analysis on the effect of using a wide range of different supply voltage values on the reliability, latency, and retention characteristics of DDR3L DRAM SO-DIMMs

einsim icon 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.

fasthash icon fasthash

Source code for the mrFAST DNA read mapper with FastHASH filtering mechanism for sequence alignment. Described in the BMC Genomics journal paper (2013) by Xin et al. http://www.biomedcentral.com/1471-2164/14/S1/S13/

fastremap icon fastremap

FastRemap, a C++ tool for quickly remapping reads between genome assemblies based on the commonly used CrossMap tool. Link to paper: https://arxiv.org/pdf/2201.06255.pdf

fcdram icon fcdram

Source code & scripts for experimental characterization and demonstration of performing NOT and up to 16-input AND, NAND, OR, and NOR operations in real DDR4 DRAM chips. Described in our HPCA'24 paper by Yuksel et al. at https://arxiv.org/abs/2402.18736

gateseeder icon 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.

genasm icon genasm

Source code for the software implementations of the GenASM algorithms proposed in our MICRO 2020 paper: Senol Cali et. al., "GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis" at https://people.inf.ethz.ch/omutlu/pub/GenASM-approximate-string-matching-framework-for-genome-analysis_micro20.pdf

genome-on-diet icon 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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