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ORCID56th MICRO 2023: Toronto, ON, Canada
- Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2023, Toronto, ON, Canada, 28 October 2023 - 1 November 2023. ACM 2023
Best Paper Session
- Toru Koizumi
, Ryota Shioya, Shu Sugita, Taichi Amano, Yuya Degawa, Junichiro Kadomoto, Hidetsugu Irie, Shuichi Sakai:
Clockhands: Rename-free Instruction Set Architecture for Out-of-order Processors. 1-16 - Ajeya Naithani, Jaime Roelandts, Sam Ainsworth, Timothy M. Jones, Lieven Eeckhout:
Decoupled Vector Runahead. 17-31 - Faiz Alam, Hyokeun Lee, Abhishek Bhattacharjee, Amro Awad:
CryptoMMU: Enabling Scalable and Secure Access Control of Third-Party Accelerators. 32-48 - Johannes Wikner, Daniël Trujillo, Kaveh Razavi:
Phantom: Exploiting Decoder-detectable Mispredictions. 49-61
Session 1A: Accelerators Based on HW/SW Co-Design Accelerators for Matrix Processing
- Seah Kim, Jerry Zhao, Krste Asanovic, Borivoje Nikolic, Yakun Sophia Shao:
AuRORA: Virtualized Accelerator Orchestration for Multi-Tenant Workloads. 62-76 - Bahador Rashidi, Chao Gao, Shan Lu, Zhisheng Wang, Chunhua Zhou, Di Niu, Fengyu Sun:
UNICO: Unified Hardware Software Co-Optimization for Robust Neural Network Acceleration. 77-90 - Axel Feldmann, Daniel Sánchez:
Spatula: A Hardware Accelerator for Sparse Matrix Factorization. 91-104
Session 1B: Architectural Support/ Programming Languages, Case Study
- Yan Sun, Yifan Yuan, Zeduo Yu, Reese Kuper, Chihun Song, Jinghan Huang, Houxiang Ji, Siddharth Agarwal, Jiaqi Lou, Ipoom Jeong, Ren Wang, Jung Ho Ahn, Tianyin Xu, Nam Sung Kim:
Demystifying CXL Memory with Genuine CXL-Ready Systems and Devices. 105-121 - Ziqi Wang, Kaiyang Zhao, Pei Li, Andrew Jacob, Michael Kozuch, Todd C. Mowry, Dimitrios Skarlatos:
Memento: Architectural Support for Ephemeral Memory Management in Serverless Environments. 122-136 - Kuan-Chieh Hsu, Hung-Wei Tseng:
Simultaneous and Heterogenous Multithreading. 137-152
Session 1C: Design Automation, Synthesis, Hardware Generation
- Fares Elsabbagh, Shabnam Sheikhha, Victor A. Ying, Quan M. Nguyen, Joel S. Emer, Daniel Sánchez:
Accelerating RTL Simulation with Hardware-Software Co-Design. 153-166 - Ceyu Xu, Pragya Sharma, Tianshu Wang, Lisa Wu Wills:
Fast, Robust and Transferable Prediction for Hardware Logic Synthesis. 167-179 - Kexing Zhou, Yun Liang, Yibo Lin, Runsheng Wang, Ru Huang:
Khronos: Fusing Memory Access for Improved Hardware RTL Simulation. 180-193
Session 2A: ML Design Space ExplorationGeneration
- Kyungmi Lee, Mengjia Yan, Joel S. Emer, Anantha P. Chandrakasan:
SecureLoop: Design Space Exploration of Secure DNN Accelerators. 194-208 - Charles Hong, Qijing Huang, Grace Dinh, Mahesh Subedar, Yakun Sophia Shao:
DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators. 209-224 - Haotian Tang, Shang Yang, Zhijian Liu, Ke Hong, Zhongming Yu, Xiuyu Li, Guohao Dai, Yu Wang, Song Han:
TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs. 225-239
Session 2B: Microarchitecture
- Arthur Perais, Rami Sheikh:
Branch Target Buffer Organizations. 240-253 - David Schall, Andreas Sandberg, Boris Grot:
Warming Up a Cold Front-End with Ignite. 254-267 - Chen Bai, Jiayi Huang, Xuechao Wei, Yuzhe Ma, Sicheng Li, Hongzhong Zheng, Bei Yu, Yuan Xie:
ArchExplorer: Microarchitecture Exploration Via Bottleneck Analysis. 268-282
Session 2C: Accelerators for Graphs, Robotics
- Shulin Zeng, Zhenhua Zhu, Jun Liu, Haoyu Zhang, Guohao Dai, Zixuan Zhou, Shuangchen Li, Xuefei Ning, Yuan Xie, Huazhong Yang, Yu Wang:
DF-GAS: a Distributed FPGA-as-a-Service Architecture towards Billion-Scale Graph-based Approximate Nearest Neighbor Search. 283-296 - Yuxin Yang, Xiaoming Chen, Yinhe Han:
Dadu-RBD: Robot Rigid Body Dynamics Accelerator with Multifunctional Pipelines. 297-309 - Chao Gao, Mahbod Afarin, Shafiur Rahman, Nael B. Abu-Ghazaleh, Rajiv Gupta:
MEGA Evolving Graph Accelerator. 310-323
Session 3A: ML Sparsity
- Ashish Gondimalla, Mithuna Thottethodi, T. N. Vijaykumar:
Eureka: Efficient Tensor Cores for One-sided Unstructured Sparsity in DNN Inference. 324-337 - Guyue Huang, Zhengyang Wang, Po-An Tsai, Chen Zhang, Yufei Ding, Yuan Xie:
RM-STC: Row-Merge Dataflow Inspired GPU Sparse Tensor Core for Energy-Efficient Sparse Acceleration. 338-352 - Hongxiang Fan, Stylianos I. Venieris, Alexandros Kouris, Nicholas D. Lane:
Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads. 353-366
Session 3B: GPUs
- Seunghwan Sung, Sujin Hur, Sungwoo Kim, Dongho Ha, Yunho Oh, Won Woo Ro:
MAD MAcce: Supporting Multiply-Add Operations for Democratizing Matrix-Multiplication Accelerators. 367-379 - Ying Li, Yifan Sun, Adwait Jog:
Path Forward Beyond Simulators: Fast and Accurate GPU Execution Time Prediction for DNN Workloads. 380-394 - Haoyang Zhang, Yirui Eric Zhou, Yuqi Xue, Yiqi Liu, Jian Huang:
G10: Enabling An Efficient Unified GPU Memory and Storage Architecture with Smart Tensor Migrations. 395-410
Session 4A: ML Architecture
- Renhao Fan, Yikai Cui, Qilin Chen, Mingyu Wang, Youhui Zhang, Weimin Zheng, Zhaolin Li:
MAICC : A Lightweight Many-core Architecture with In-Cache Computing for Multi-DNN Parallel Inference. 411-423 - Hongrui Guo, Yongwei Zhao, Zhangmai Li, Yifan Hao, Chang Liu, Xinkai Song, Xiaqing Li, Zidong Du, Rui Zhang, Qi Guo, Tianshi Chen, Zhiwei Xu:
Cambricon-U: A Systolic Random Increment Memory Architecture for Unary Computing. 424-437 - Jungwoo Kim, Seonjin Na, Sanghyeon Lee, Sunho Lee, Jaehyuk Huh:
Improving Data Reuse in NPU On-chip Memory with Interleaved Gradient Order for DNN Training. 438-451 - Zheng Qu, Dimin Niu, Shuangchen Li, Hongzhong Zheng, Yuan Xie:
TT-GNN: Efficient On-Chip Graph Neural Network Training via Embedding Reformation and Hardware Optimization. 452-464 - Uday Kumar Reddy Vengalam, Yongchao Liu, Tong Geng, Hui Wu, Michael C. Huang:
Supporting Energy-based Learning with an Ising Machine substrate: a Case Study on RBM. 465-478
Session 4B: Quantum
- Anbang Wu, Yufei Ding, Ang Li:
QuComm: Optimizing Collective Communication for Distributed Quantum Computing. 479-493 - Siwei Tan, Congliang Lang, Liang Xiang, Shudi Wang, Xinghui Jia, Ziqi Tan, Tingting Li, Jieming Yin, Yongheng Shang, Andre Python, Liqiang Lu, Jianwei Yin:
QuCT: A Framework for Analyzing Quantum Circuit by Extracting Contextual and Topological Features. 494-508 - Suhas Vittal, Poulami Das, Moinuddin K. Qureshi:
ERASER: Towards Adaptive Leakage Suppression for Fault-Tolerant Quantum Computing. 509-525 - Shifan Xu, Connor T. Hann, Ben Foxman, Steven M. Girvin, Yongshan Ding:
Systems Architecture for Quantum Random Access Memory. 526-538 - Samuel Alexander Stein, Sara Sussman, Teague Tomesh, Charles Guinn, Esin Tureci, Sophia Fuhui Lin, Wei Tang, James A. Ang, Srivatsan Chakram, Ang Li, Margaret Martonosi, Fred Chong, Andrew A. Houck, Isaac L. Chuang, Michael Austin DeMarco:
HetArch: Heterogeneous Microarchitectures for Superconducting Quantum Systems. 539-554
Session 4C: Emerging Technologies: Superconducting, Photonics, DNA
- Puru Sharma, Cheng-Kai Lim, Dehui Lin, Yash Pote, Djordje Jevdjic:
Efficiently Enabling Block Semantics and Data Updates in DNA Storage. 555-568 - Shurui Li, Hangbo Yang, Chee Wei Wong, Volker J. Sorger, Puneet Gupta:
ReFOCUS: Reusing Light for Efficient Fourier Optics-Based Photonic Neural Network Accelerator. 569-583 - Zhengang Li, Geng Yuan, Tomoharu Yamauchi, Masoud Zabihi, Yanyue Xie, Peiyan Dong, Xulong Tang, Nobuyuki Yoshikawa, Devesh Tiwari, Yanzhi Wang, Olivia Chen:
SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices. 584-598 - Haipeng Zha, Swamit Tannu, Murali Annavaram:
SuperBP: Design Space Exploration of Perceptron-Based Branch Predictors for Superconducting CPUs. 599-613 - Zeshi Liu, Shuo Chen, Peiyao Qu, Huanli Liu, Minghui Niu, Liliang Ying, Jie Ren, Guangming Tang, Haihang You:
SUSHI: Ultra-High-Speed and Ultra-Low-Power Neuromorphic Chip Using Superconducting Single-Flux-Quantum Circuits. 614-627
Session 5A: Security Encryption/Confidentiality Support
- Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu:
AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. 628-640 - Saar Amar, David Chisnall, Tony Chen, Nathaniel Wesley Filardo, Ben Laurie, Kunyan Liu, Robert M. Norton, Simon W. Moore, Yucong Tao, Robert N. M. Watson, Hongyan Xia:
CHERIoT: Complete Memory Safety for Embedded Devices. 641-653 - Dong Du, Bicheng Yang, Yubin Xia, Haibo Chen:
Accelerating Extra Dimensional Page Walks for Confidential Computing. 654-669 - Kaustubh Shivdikar, Yuhui Bao, Rashmi Agrawal, Michael Tian Shen, Gilbert Jonatan, Evelio Mora, Alexander Ingare, Neal Livesay, José L. Abellán, John Kim, Ajay Joshi, David R. Kaeli:
GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption. 670-684 - Rashmi Agrawal, Leo de Castro, Chiraag Juvekar, Anantha P. Chandrakasan, Vinod Vaikuntanathan, Ajay Joshi:
MAD: Memory-Aware Design Techniques for Accelerating Fully Homomorphic Encryption. 685-697
Session 5B: Prefetching
- Gerasimos Gerogiannis, Josep Torrellas:
Micro-Armed Bandit: Lightweight & Reusable Reinforcement Learning for Microarchitecture Decision-Making. 698-713 - Biswabandan Panda:
CLIP: Load Criticality based Data Prefetching for Bandwidth-constrained Many-core Systems. 714-727 - Saba Mostofi, Hajar Falahati, Negin Mahani, Pejman Lotfi-Kamran, Hamid Sarbazi-Azad:
Snake: A Variable-length Chain-based Prefetching for GPUs. 728-741 - Yuan-Hsi Chou, Tyler Nowicki, Tor M. Aamodt:
Treelet Prefetching For Ray Tracing. 742-755
Session 5C: Processing-In-Memory
- Qiyu Wan, Lening Wang, Jing Wang, Shuaiwen Leon Song, Xin Fu:
NAS-SE: Designing A Highly-Efficient In-Situ Neural Architecture Search Engine for Large-Scale Deployment. 756-768 - Neel Patel, Amin Mamandipoor, Derrick Quinn, Mohammad Alian:
XFM: Accelerated Software-Defined Far Memory. 769-783 - Zhengrong Wang, Christopher Liu, Nathan Beckmann, Tony Nowatzki:
Affinity Alloc: Taming Not-So Near-Data Computing. 784-799 - Daichi Fujiki:
MVC: Enabling Fully Coherent Multi-Data-Views through the Memory Hierarchy with Processing in Memory. 800-814 - Hongju Kal, Chanyoung Yoo, Won Woo Ro:
AESPA: Asynchronous Execution Scheme to Exploit Bank-Level Parallelism of Processing-in-Memory. 815-827
Session 6A: Security Hardware
- Pavlos Aimoniotis, Amund Bergland Kvalsvik, Xiaoyue Chen, Magnus Själander, Stefanos Kaxiras:
ReCon: Efficient Detection, Management, and Use of Non-Speculative Information Leakage. 828-842 - Yanan Guo, Dingyuan Cao, Xin Xin, Youtao Zhang, Jun Yang:
Uncore Encore: Covert Channels Exploiting Uncore Frequency Scaling. 843-855 - Yuanqing Miao, Mahmut Taylan Kandemir, Danfeng Zhang, Yingtian Zhang, Gang Tan, Dinghao Wu:
Hardware Support for Constant-Time Programming. 856-870 - Marcelo Orenes-Vera, Hyunsung Yun, Nils Wistoff, Gernot Heiser, Luca Benini, David Wentzlaff, Margaret Martonosi:
AutoCC: Automatic Discovery of Covert Channels in Time-Shared Hardware. 871-885
Session 6B: Datacenter Networks
- Alon Rashelbach, Igor Lima de Paula, Mark Silberstein:
NeuroLPM - Scaling Longest Prefix Match Hardware with Neural Networks. 886-899 - Nathaniel Bleier, Muhammad Husnain Mubarik, Gary R. Swenson, Rakesh Kumar:
Space Microdatacenters. 900-915 - Zerui Guo, Jiaxin Lin, Yuebin Bai, Daehyeok Kim, Michael M. Swift, Aditya Akella, Ming Liu:
LogNIC: A High-Level Performance Model for SmartNICs. 916-929 - Yinxiao Feng, Dong Xiang, Kaisheng Ma:
Heterogeneous Die-to-Die Interfaces: Enabling More Flexible Chiplet Interconnection Systems. 930-943
Session 6C: Reliability, Availability
- Jeageun Jung, Mattan Erez:
Predicting Future-System Reliability with a Component-Level DRAM Fault Model. 944-956 - Dimitris Agiakatsikas, George Papadimitriou, Vasileios Karakostas, Dimitris Gizopoulos, Mihalis Psarakis, Camille Bélanger-Champagne, Ewart Blackmore:
Impact of Voltage Scaling on Soft Errors Susceptibility of Multicore Server CPUs. 957-971 - Edward Hanson, Shiyu Li, Guanglei Zhou, Feng Cheng, Yitu Wang, Rohan Bose, Hai Li, Yiran Chen:
Si-Kintsugi: Towards Recovering Golden-Like Performance of Defective Many-Core Spatial Architectures for AI. 972-985 - Michael Jaemin Kim, Minbok Wi, Jaehyun Park, Seoyoung Ko, Jaeyoung Choi, Hwayong Nam, Nam Sung Kim, Jung Ho Ahn, Eojin Lee:
How to Kill the Second Bird with One ECC: The Pursuit of Row Hammer Resilient DRAM. 986-1001
Session 7A: Accelerators Various
- Yun-Chen Lo, Ren-Shuo Liu:
Bucket Getter: A Bucket-based Processing Engine for Low-bit Block Floating Point (BFP) DNNs. 1002-1015 - Andrew McCrabb, Aymen Ahmed, Valeria Bertacco:
ACRE: Accelerating Random Forests for Explainability. 1016-1028 - Raúl Taranco, José-María Arnau, Antonio González:
δLTA: Decoupling Camera Sampling from Processing to Avoid Redundant Computations in the Vision Pipeline. 1029-1043
Session 7B: Caches, Intermitent Computing, Persistency
- Jaewon Kwon, Yongju Lee, Hongju Kal, Minjae Kim, Youngsok Kim, Won Woo Ro:
McCore: A Holistic Management of High-Performance Heterogeneous Multicores. 1044-1058 - Yuchen Zhou, Jianping Zeng, Jungi Jeong, Jongouk Choi, Changhee Jung:
SweepCache: Intermittence-Aware Cache on the Cheap. 1059-1074 - Jianping Zeng, Jungi Jeong, Changhee Jung:
Persistent Processor Architecture. 1075-1091
Session 8A: Accelerators for Neural Nets Accelerators for Matrix Processing
- Vahid Janfaza, Shantanu Mandal, Farabi Mahmud, Abdullah Muzahid:
ADA-GP: Accelerating DNN Training By Adaptive Gradient Prediction. 1092-1105 - Yannan Nellie Wu, Po-An Tsai, Saurav Muralidharan, Angshuman Parashar, Vivienne Sze, Joel S. Emer:
HighLight: Efficient and Flexible DNN Acceleration with Hierarchical Structured Sparsity. 1106-1120 - Hyunwuk Lee, Hyungjun Jang, Sungbin Kim, Sungwoo Kim, Wonho Cho, Won Woo Ro:
Exploiting Inherent Properties of Complex Numbers for Accelerating Complex Valued Neural Networks. 1121-1134 - Cen Chen, Xiaofeng Zou, Hongen Shao, Yangfan Li, Kenli Li:
Point Cloud Acceleration by Exploiting Geometric Similarity. 1135-1147 - Jinkwon Kim, Myeongjae Jang, Haejin Nam, Soontae Kim:
HARP: Hardware-Based Pseudo-Tiling for Sparse Matrix Multiplication Accelerator. 1148-1162
Session 8B: Virtual Memory (Translation)
- Bingyao Li, Yanan Guo, Yueqi Wang, Aamer Jaleel, Jun Yang, Xulong Tang:
IDYLL: Enhancing Page Translation in Multi-GPUs via Light Weight PTE Invalidations. 1163-1177 - Konstantinos Kanellopoulos, Hong Chul Nam, Nisa Bostanci, Rahul Bera, Mohammad Sadrosadati, Rakesh Kumar, Davide Basilio Bartolini, Onur Mutlu:
Victima: Drastically Increasing Address Translation Reach by Leveraging Underutilized Cache Resources. 1178-1195 - Konstantinos Kanellopoulos, Rahul Bera, Kosta Stojiljkovic, F. Nisa Bostanci, Can Firtina, Rachata Ausavarungnirun, Rakesh Kumar, Nastaran Hajinazar, Mohammad Sadrosadati, Nandita Vijaykumar, Onur Mutlu:
Utopia: Fast and Efficient Address Translation via Hybrid Restrictive & Flexible Virtual-to-Physical Address Mappings. 1196-1212 - Aninda Manocha, Zi Yan, Esin Tureci, Juan L. Aragón, David W. Nellans, Margaret Martonosi:
Architectural Support for Optimizing Huge Page Selection Within the OS. 1213-1226
Session 8C: Benchmarking and Methodology
- Changxi Liu, Yifan Sun, Trevor E. Carlson:
Photon: A Fine-grained Sampled Simulation Methodology for GPU Workloads. 1227-1241 - Filip Mazurek, Arya Tschand, Yu Wang, Miroslav Pajic, Daniel J. Sorin:
Rigorous Evaluation of Computer Processors with Statistical Model Checking. 1242-1254 - Nandeeka Nayak, Toluwanimi O. Odemuyiwa, Shubham Ugare, Christopher W. Fletcher, Michael Pellauer, Joel S. Emer:
TeAAL: A Declarative Framework for Modeling Sparse Tensor Accelerators. 1255-1270 - Size Zheng, Siyuan Chen, Siyuan Gao, Liancheng Jia, Guangyu Sun, Runsheng Wang, Yun Liang:
TileFlow: A Framework for Modeling Fusion Dataflow via Tree-based Analysis. 1271-1288 - Daixuan Li, Jinghan Sun, Jian Huang:
Learning to Drive Software-Defined Solid-State Drives. 1289-1304
Session 9A: Accelerators in Processors
- Xinkai Song, Yuanbo Wen, Xing Hu, Tianbo Liu, Haoxuan Zhou, Husheng Han, Tian Zhi, Zidong Du, Wei Li, Rui Zhang, Chen Zhang, Lin Gao, Qi Guo, Tianshi Chen:
Cambricon-R: A Fully Fused Accelerator for Real-Time Learning of Neural Scene Representation. 1305-1318 - Adiwena Putra, Prasetiyo, Yi Chen, John Kim, Joo-Young Kim:
Strix: An End-to-End Streaming Architecture with Two-Level Ciphertext Batching for Fully Homomorphic Encryption with Programmable Bootstrapping. 1319-1331 - Marco Siracusa, Víctor Soria Pardos, Francesco Sgherzi, Joshua Randall, Douglas J. Joseph, Miquel Moretó Planas, Adrià Armejach:
A Tensor Marshaling Unit for Sparse Tensor Algebra on General-Purpose Processors. 1332-1346 - Zi Yu Xue, Yannan Nellie Wu, Joel S. Emer, Vivienne Sze:
Tailors: Accelerating Sparse Tensor Algebra by Overbooking Buffer Capacity. 1347-1363
Session 9B: ML Compiler Optimizations/ Reconfigurable Architectures
- Bojian Zheng, Cody Hao Yu, Jie Wang, Yaoyao Ding, Yizhi Liu, Yida Wang, Gennady Pekhimenko:
Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUs. 1364-1380 - Ligeng Zhu, Lanxiang Hu, Ji Lin, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han:
PockEngine: Sparse and Efficient Fine-tuning in a Pocket. 1381-1394 - Jinyi Deng, Xinru Tang, Jiahao Zhang, Yuxuan Li, Linyun Zhang, Boxiao Han, Hongjun He, Fengbin Tu, Leibo Liu, Shaojun Wei, Yang Hu, Shouyi Yin:
Towards Efficient Control Flow Handling in Spatial Architecture via Architecting the Control Flow Plane. 1395-1408 - Nathan Serafin, Souradip Ghosh, Harsh Desai, Nathan Beckmann, Brandon Lucia:
Pipestitch: An energy-minimal dataflow architecture with lightweight threads. 1409-1422
Session 9C: Domain Specific Genomics
- Yi Huang, Lingkun Kong, Dibei Chen, Zhiyu Chen, Xiangyu Kong, Jianfeng Zhu, Konstantinos Mamouras, Shaojun Wei, Kaiyuan Yang, Leibo Liu:
CASA: An Energy-Efficient and High-Speed CAM-based SMEM Seeding Accelerator for Genome Alignment. 1423-1436 - Taha Shahroodi, Gagandeep Singh, Mahdi Zahedi, Haiyu Mao, Joël Lindegger, Can Firtina, Stephan Wong, Onur Mutlu, Said Hamdioui:
Swordfish: A Framework for Evaluating Deep Neural Network-based Basecalling using Computation-In-Memory with Non-Ideal Memristors. 1437-1452 - Zuher Jahshan, Itay Merlin, Esteban Garzón, Leonid Yavits:
DASH-CAM: Dynamic Approximate SearcH Content Addressable Memory for genome classification. 1453-1465 - Max Doblas, Oscar Lostes-Cazorla, Quim Aguado-Puig, Nick Cebry, Pau Fontova-Musté, Christopher Frances Batten, Santiago Marco-Sola, Miquel Moretó:
GMX: Instruction Set Extensions for Fast, Scalable, and Efficient Genome Sequence Alignment. 1466-1480
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