
Mohsen Imani
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2020 – today
- 2020
- [j17]Mohsen Imani
, Justin Morris
, Helen Shu, Shou Li, Tajana Rosing:
Efficient Associative Search in Brain-Inspired Hyperdimensional Computing. IEEE Des. Test 37(1): 28-35 (2020) - [j16]Sahand Salamat
, Mohsen Imani
, Tajana Rosing:
Accelerating Hyperdimensional Computing on FPGAs by Exploiting Computational Reuse. IEEE Trans. Computers 69(8): 1159-1171 (2020) - [j15]Daniel Peroni
, Mohsen Imani
, Tajana Simunic Rosing:
Runtime Efficiency-Accuracy Tradeoff Using Configurable Floating Point Multiplier. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(2): 346-358 (2020) - [j14]Mohsen Imani
, Samuel Bosch
, Sohum Datta
, Sharadhi Ramakrishna, Sahand Salamat, Jan M. Rabaey, Tajana Rosing:
QuantHD: A Quantization Framework for Hyperdimensional Computing. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2268-2278 (2020) - [j13]Mohsen Imani
, Xunzhao Yin
, John Messerly, Saransh Gupta
, Michael T. Niemier
, Xiaobo Sharon Hu
, Tajana Rosing:
SearcHD: A Memory-Centric Hyperdimensional Computing With Stochastic Training. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2422-2433 (2020) - [j12]Daniel Peroni
, Mohsen Imani
, Hamid Nejatollahi
, Nikil D. Dutt
, Tajana Rosing:
Data Reuse for Accelerated Approximate Warps. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(12): 4623-4634 (2020) - [c74]Behnam Khaleghi, Mohsen Imani, Tajana Rosing:
Prive-HD: Privacy-Preserved Hyperdimensional Computing. DAC 2020: 1-6 - [c73]Hamid Nejatollahi, Saransh Gupta, Mohsen Imani, Tajana Simunic Rosing, Rosario Cammarota, Nikil D. Dutt
:
CryptoPIM: In-memory Acceleration for Lattice-based Cryptographic Hardware. DAC 2020: 1-6 - [c72]Yeseong Kim, Mohsen Imani, Niema Moshiri, Tajana Rosing:
GenieHD: Efficient DNA Pattern Matching Accelerator Using Hyperdimensional Computing. DATE 2020: 115-120 - [c71]Saransh Gupta, Mohsen Imani, Joonseop Sim, Andrew Huang, Fan Wu, M. Hassan Najafi, Tajana Rosing:
SCRIMP: A General Stochastic Computing Architecture using ReRAM in-Memory Processing. DATE 2020: 1598-1601 - [c70]Mohsen Imani, Mohammad Samragh Razlighi, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing:
Deep Learning Acceleration with Neuron-to-Memory Transformation. HPCA 2020: 1-14 - [c69]Chuangtao Chen, Sen Yang, Weikang Qian, Mohsen Imani, Xunzhao Yin, Cheng Zhuo:
Optimally Approximated and Unbiased Floating-Point Multiplier with Runtime Configurability. ICCAD 2020: 1-9 - [c68]Saransh Gupta, Justin Morris, Mohsen Imani, Ranganathan Ramkumar, Jeffrey Yu, Aniket Tiwari, Baris Aksanli, Tajana Simunic Rosing:
THRIFTY: Training with Hyperdimensional Computing across Flash Hierarchy. ICCAD 2020: 1-9 - [c67]Saransh Gupta, Mohsen Imani, Hengyu Zhao, Fan Wu, Jishen Zhao, Tajana Simunic Rosing:
Implementing binary neural networks in memory with approximate accumulation. ISLPED 2020: 247-252 - [c66]Mohsen Imani, Saikishan Pampana, Saransh Gupta, Minxuan Zhou, Yeseong Kim, Tajana Rosing:
DUAL: Acceleration of Clustering Algorithms using Digital-based Processing In-Memory. MICRO 2020: 356-371 - [i14]Behnam Khaleghi, Mohsen Imani, Tajana Rosing:
Prive-HD: Privacy-Preserved Hyperdimensional Computing. CoRR abs/2005.06716 (2020) - [i13]Rosario Cammarota, Matthias Schunter, Anand Rajan, Fabian Boemer, Ágnes Kiss, Amos Treiber, Christian Weinert, Thomas Schneider, Emmanuel Stapf, Ahmad-Reza Sadeghi, Daniel Demmler, Huili Chen, Siam Umar Hussain, M. Sadegh Riazi, Farinaz Koushanfar, Saransh Gupta, Tajana Simunic Rosing, Kamalika Chaudhuri, Hamid Nejatollahi, Nikil D. Dutt, Mohsen Imani, Kim Laine, Anuj Dubey, Aydin Aysu, Fateme Sadat Hosseini, Chengmo Yang, Eric Wallace, Pamela Norton:
Trustworthy AI Inference Systems: An Industry Research View. CoRR abs/2008.04449 (2020) - [i12]Hamid Nejatollahi, Saransh Gupta, Mohsen Imani, Tajana Simunic Rosing, Rosario Cammarota, Nikil D. Dutt:
CryptoPIM: In-memory Acceleration for Lattice-based Cryptographic Hardware. IACR Cryptol. ePrint Arch. 2020: 276 (2020)
2010 – 2019
- 2019
- [j11]Mohsen Imani, Mehrdad Amirabadi, Matthew Wright:
Modified relay selection and circuit selection for faster Tor. IET Commun. 13(17): 2723-2734 (2019) - [j10]Mohsen Imani, Ricardo Garcia, Saransh Gupta, Tajana Rosing:
Hardware-Software Co-design to Accelerate Neural Network Applications. ACM J. Emerg. Technol. Comput. Syst. 15(2): 21:1-21:18 (2019) - [j9]Yeseong Kim, Mohsen Imani, Tajana Simunic Rosing:
Image Recognition Accelerator Design Using In-Memory Processing. IEEE Micro 39(1): 17-23 (2019) - [j8]Saransh Gupta
, Mohsen Imani
, Harveen Kaur, Tajana Simunic Rosing:
NNPIM: A Processing In-Memory Architecture for Neural Network Acceleration. IEEE Trans. Computers 68(9): 1325-1337 (2019) - [j7]Mohsen Imani
, Saransh Gupta
, Sahil Sharma, Tajana Simunic Rosing:
NVQuery: Efficient Query Processing in Nonvolatile Memory. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(4): 628-639 (2019) - [j6]Mohsen Imani
, Daniel Peroni
, Abbas Rahimi, Tajana Simunic Rosing:
Resistive CAM Acceleration for Tunable Approximate Computing. IEEE Trans. Emerg. Top. Comput. 7(2): 271-280 (2019) - [c65]Mohsen Imani, Yeseong Kim, M. Sadegh Riazi, John Messerly, Patric Liu, Farinaz Koushanfar, Tajana Rosing:
A Framework for Collaborative Learning in Secure High-Dimensional Space. CLOUD 2019: 435-446 - [c64]Mohsen Imani, Sahand Salamat, Saransh Gupta
, Jiani Huang, Tajana Rosing:
FACH: FPGA-based acceleration of hyperdimensional computing by reducing computational complexity. ASP-DAC 2019: 493-498 - [c63]Minxuan Zhou, Mohsen Imani, Saransh Gupta
, Yeseong Kim, Tajana Rosing:
GRAM: graph processing in a ReRAM-based computational memory. ASP-DAC 2019: 591-596 - [c62]Daniel Peroni, Mohsen Imani, Tajana Rosing:
ALook: adaptive lookup for GPGPU acceleration. ASP-DAC 2019: 739-746 - [c61]Mohsen Imani, Justin Morris, Samuel Bosch
, Helen Shu, Giovanni De Micheli, Tajana Rosing:
AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing. BioCAS 2019: 1-4 - [c60]Daniel Peroni, Mohsen Imani, Hamid Nejatollahi, Nikil D. Dutt
, Tajana Rosing:
ARGA: Approximate Reuse for GPGPU Acceleration. DAC 2019: 8 - [c59]Mohsen Imani, Justin Morris, John Messerly, Helen Shu, Yaobang Deng, Tajana Rosing:
BRIC: Locality-based Encoding for Energy-Efficient Brain-Inspired Hyperdimensional Computing. DAC 2019: 52 - [c58]Mohsen Imani, Alice Sokolova, Ricardo Garcia, Andrew Huang, Fan Wu, Baris Aksanli, Tajana Rosing:
ApproxLP: Approximate Multiplication with Linearization and Iterative Error Control. DAC 2019: 159 - [c57]Minxuan Zhou, Mohsen Imani, Saransh Gupta, Tajana Rosing:
Thermal-Aware Design and Management for Search-based In-Memory Acceleration. DAC 2019: 174 - [c56]Mohsen Imani, John Messerly, Fan Wu, Wang Pi, Tajana Rosing:
A Binary Learning Framework for Hyperdimensional Computing. DATE 2019: 126-131 - [c55]Mohsen Imani, Ricardo Garcia, Andrew Huang, Tajana Rosing:
CADE: Configurable Approximate Divider for Energy Efficiency. DATE 2019: 586-589 - [c54]Mohsen Imani, Yeseong Kim, Thomas Worley, Saransh Gupta, Tajana Rosing:
HDCluster: An Accurate Clustering Using Brain-Inspired High-Dimensional Computing. DATE 2019: 1591-1594 - [c53]Mohsen Imani, Sahand Salamat, Behnam Khaleghi, Mohammad Samragh, Farinaz Koushanfar, Tajana Rosing:
SparseHD: Algorithm-Hardware Co-optimization for Efficient High-Dimensional Computing. FCCM 2019: 190-198 - [c52]Sahand Salamat, Mohsen Imani, Behnam Khaleghi, Tajana Rosing:
F5-HD: Fast Flexible FPGA-based Framework for Refreshing Hyperdimensional Computing. FPGA 2019: 53-62 - [c51]Saransh Gupta, Mohsen Imani, Tajana Rosing:
Exploring Processing In-Memory for Different Technologies. ACM Great Lakes Symposium on VLSI 2019: 201-206 - [c50]Joonseop Sim, Saransh Gupta, Mohsen Imani, Yeseong Kim, Tajana Rosing:
UPIM: Unipolar Switching Logic for High Density Processing-in-Memory Applications. ACM Great Lakes Symposium on VLSI 2019: 255-258 - [c49]Mohsen Imani, Saransh Gupta, Yeseong Kim, Minxuan Zhou, Tajana Rosing:
DigitalPIM: Digital-based Processing In-Memory for Big Data Acceleration. ACM Great Lakes Symposium on VLSI 2019: 429-434 - [c48]Mohsen Imani, Samuel Bosch
, Mojan Javaheripi, Bita Darvish Rouhani, Xinyu Wu, Farinaz Koushanfar, Tajana Rosing:
SemiHD: Semi-Supervised Learning Using Hyperdimensional Computing. ICCAD 2019: 1-8 - [c47]Sahand Salamat, Behnam Khaleghi, Mohsen Imani, Tajana Rosing:
Workload-Aware Opportunistic Energy Efficiency in Multi-FPGA Platforms. ICCAD 2019: 1-8 - [c46]Behnam Khaleghi, Sahand Salamat, Mohsen Imani, Tajana Rosing:
FPGA Energy Efficiency by Leveraging Thermal Margin. ICCD 2019: 376-384 - [c45]Mohsen Imani, Saransh Gupta, Yeseong Kim, Tajana Rosing:
FloatPIM: in-memory acceleration of deep neural network training with high precision. ISCA 2019: 802-815 - [c44]Saransh Gupta, Mohsen Imani, Behnam Khaleghi, Venkatesh Kumar, Tajana Rosing:
RAPID: A ReRAM Processing in-Memory Architecture for DNA Sequence Alignment. ISLPED 2019: 1-6 - [c43]Justin Morris, Mohsen Imani, Samuel Bosch
, Anthony Thomas, Helen Shu, Tajana Rosing:
CompHD: Efficient Hyperdimensional Computing Using Model Compression. ISLPED 2019: 1-6 - [c42]Mohsen Imani, Saransh Gupta, Tajana Rosing:
Digital-based processing in-memory: a highly-parallel accelerator for data intensive applications. MEMSYS 2019: 38-40 - [p1]Mohsen Imani, Tajana Simunic Rosing:
Approximate CPU and GPU Design Using Emerging Memory Technologies. Approximate Circuits 2019: 383-398 - [i11]Mohsen Imani, Mohammad Saidur Rahman, Nate Mathews, Aneesh Yogesh Joshi, Matthew Wright:
Adv-DWF: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces. CoRR abs/1902.06626 (2019) - [i10]Sahand Salamat, Behnam Khaleghi, Mohsen Imani, Tajana Rosing:
Workload-Aware Opportunistic Energy Efficiency in Multi-FPGA Platforms. CoRR abs/1908.06519 (2019) - [i9]Behnam Khaleghi, Sahand Salamat, Mohsen Imani, Tajana Rosing:
FPGA Energy Efficiency by Leveraging Thermal Margin. CoRR abs/1911.07187 (2019) - [i8]Samuel Bosch, Alexander Sanchez de la Cerda, Mohsen Imani, Tajana Simunic Rosing, Giovanni De Micheli:
QubitHD: A Stochastic Acceleration Method for HD Computing-Based Machine Learning. CoRR abs/1911.12446 (2019) - 2018
- [j5]Mohsen Imani
, Daniel Peroni, Tajana Rosing:
Nvalt: Nonvolatile Approximate Lookup Table for GPU Acceleration. IEEE Embed. Syst. Lett. 10(1): 14-17 (2018) - [j4]Mohsen Imani, Armon Barton, Matthew Wright:
Guard Sets in Tor using AS Relationships. Proc. Priv. Enhancing Technol. 2018(1): 145-165 (2018) - [j3]Mohsen Imani
, Shruti Patil, Tajana Simunic Rosing:
Approximate Computing Using Multiple-Access Single-Charge Associative Memory. IEEE Trans. Emerg. Top. Comput. 6(3): 305-316 (2018) - [j2]Mohsen Imani
, Abbas Rahimi, Pietro Mercati, Tajana Simunic Rosing:
Multi-Stage Tunable Approximate Search in Resistive Associative Memory. IEEE Trans. Multi Scale Comput. Syst. 4(1): 17-29 (2018) - [c41]Mohsen Imani, Max Masich, Daniel Peroni, Pushen Wang, Tajana Rosing:
CANNA: Neural network acceleration using configurable approximation on GPGPU. ASP-DAC 2018: 682-689 - [c40]Mohsen Imani, Tarek Nassar, Abbas Rahimi, Tajana Rosing:
HDNA: Energy-efficient DNA sequencing using hyperdimensional computing. BHI 2018: 271-274 - [c39]Payap Sirinam, Mohsen Imani, Marc Juárez, Matthew Wright:
Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning. CCS 2018: 1928-1943 - [c38]Mohsen Imani, Mohammad Saidur Rahman, Matthew Wright:
Adversarial Traces for Website Fingerprinting Defense. CCS 2018: 2225-2227 - [c37]Mohsen Imani, Chenyu Huang, Deqian Kong, Tajana Rosing:
Hierarchical hyperdimensional computing for energy efficient classification. DAC 2018: 108:1-108:6 - [c36]Mohsen Imani, Saransh Gupta
, Tajana Rosing:
GenPIM: Generalized processing in-memory to accelerate data intensive applications. DATE 2018: 1155-1158 - [c35]Saransh Gupta
, Mohsen Imani, Tajana Rosing:
FELIX: fast and energy-efficient logic in memory. ICCAD 2018: 55 - [c34]Sahand Salamat, Mohsen Imani, Saransh Gupta
, Tajana Rosing:
RNSnet: In-Memory Neural Network Acceleration Using Residue Number System. ICRC 2018: 1-12 - [c33]Yeseong Kim, Mohsen Imani, Tajana Simunic Rosing:
Efficient human activity recognition using hyperdimensional computing. IOT 2018: 38:1-38:6 - [c32]Mohsen Imani, Ricardo Garcia, Saransh Gupta
, Tajana Rosing:
RMAC: Runtime Configurable Floating Point Multiplier for Approximate Computing. ISLPED 2018: 12:1-12:6 - [c31]Minxuan Zhou, Mohsen Imani, Saransh Gupta
, Tajana Rosing:
GAS: A Heterogeneous Memory Architecture for Graph Processing. ISLPED 2018: 27:1-27:6 - [c30]Mohsen Imani, Daniel Peroni, Tajana Rosing:
Program acceleration using nearest distance associative search. ISQED 2018: 43-48 - [c29]Joonseop Sim, Mohsen Imani, Woojin Choi, Yeseong Kim, Tajana Rosing:
LUPIS: Latch-up based ultra efficient processing in-memory system. ISQED 2018: 55-60 - [c28]Mohsen Imani, Pushen Wang, Tajana Rosing:
Deep neural network acceleration framework under hardware uncertainty. ISQED 2018: 389-394 - [c27]Armon Barton, Matthew Wright, Jiang Ming, Mohsen Imani:
Towards Predicting Efficient and Anonymous Tor Circuits. USENIX Security Symposium 2018: 429-444 - [i7]Payap Sirinam, Mohsen Imani, Marc Juárez, Matthew Wright:
Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning. CoRR abs/1801.02265 (2018) - [i6]Armon Barton, Mohsen Imani, Jiang Ming, Matthew Wright:
Towards Predicting Efficient and Anonymous Tor Circuits. CoRR abs/1805.01977 (2018) - [i5]Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing:
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework. CoRR abs/1806.05794 (2018) - 2017
- [j1]Mohsen Imani
, John Hwang, Tajana Rosing, Abbas Rahimi, Jan M. Rabaey:
Low-Power Sparse Hyperdimensional Encoder for Language Recognition. IEEE Des. Test 34(6): 94-101 (2017) - [c26]Mohsen Imani, Yeseong Kim, Tajana Rosing:
MPIM: Multi-purpose in-memory processing using configurable resistive memory. ASP-DAC 2017: 757-763 - [c25]Mohsen Imani, Saransh Gupta
, Tajana Rosing:
Ultra-Efficient Processing In-Memory for Data Intensive Applications. DAC 2017: 6:1-6:6 - [c24]Mohsen Imani, Daniel Peroni, Tajana Rosing:
CFPU: Configurable Floating Point Multiplier for Energy-Efficient Computing. DAC 2017: 76:1-76:6 - [c23]Mohsen Imani, Daniel Peroni, Yeseong Kim, Abbas Rahimi, Tajana Rosing:
Efficient neural network acceleration on GPGPU using content addressable memory. DATE 2017: 1026-1031 - [c22]Mohammad Samragh Razlighi, Mohsen Imani, Farinaz Koushanfar, Tajana Rosing:
LookNN: Neural network with no multiplication. DATE 2017: 1775-1780 - [c21]Mohsen Imani, Abbas Rahimi, Deqian Kong, Tajana Rosing, Jan M. Rabaey:
Exploring Hyperdimensional Associative Memory. HPCA 2017: 445-456 - [c20]Yeseong Kim, Mohsen Imani, Tajana Rosing:
ORCHARD: Visual object recognition accelerator based on approximate in-memory processing. ICCAD 2017: 25-32 - [c19]Mohsen Imani, Yeseong Kim, Tajana Rosing:
NNgine: Ultra-Efficient Nearest Neighbor Accelerator Based on In-Memory Computing. ICRC 2017: 1-8 - [c18]Mohsen Imani, Deqian Kong, Abbas Rahimi, Tajana Rosing:
VoiceHD: Hyperdimensional Computing for Efficient Speech Recognition. ICRC 2017: 1-8 - [c17]Mohsen Imani, Saransh Gupta
, Atl Arredondo, Tajana Rosing:
Efficient query processing in crossbar memory. ISLPED 2017: 1-6 - [c16]Mohsen Imani, Tajana Rosing:
CAP: Configurable resistive associative processor for near-data computing. ISQED 2017: 346-352 - [c15]Joonseop Sim, Mohsen Imani, Yeseong Kim, Tajana Rosing:
Enabling efficient system design using vertical nanowire transistor current mode logic. VLSI-SoC 2017: 1-6 - [i4]Mohsen Imani, Armon Barton, Matthew Wright:
Forming Guard Sets using AS Relationships. CoRR abs/1706.05592 (2017) - [i3]Mohsen Imani, Mehrdad Amirabadi, Matthew Wright:
The Evaluation of Circuit Selection Methods on Tor. CoRR abs/1706.06457 (2017) - 2016
- [c14]Mohsen Imani, Shruti Patil, Tajana Simunic Rosing:
MASC: Ultra-low energy multiple-access single-charge TCAM for approximate computing. DATE 2016: 373-378 - [c13]Mohsen Imani, Abbas Rahimi, Tajana Simunic Rosing:
Resistive configurable associative memory for approximate computing. DATE 2016: 1327-1332 - [c12]Marc Juárez, Mohsen Imani, Mike Perry, Claudia Díaz, Matthew Wright
:
Toward an Efficient Website Fingerprinting Defense. ESORICS (1) 2016: 27-46 - [c11]Mohsen Imani, Shruti Patil, Tajana Simunic Rosing:
DCC: Double Capacity Cache Architecture for Narrow-Width Values. ACM Great Lakes Symposium on VLSI 2016: 113-116 - [c10]Pietro Mercati, Francesco Paterna, Andrea Bartolini
, Mohsen Imani, Luca Benini
, Tajana Simunic Rosing:
VarDroid: Online Variability Emulation in Android/Linux Platforms. ACM Great Lakes Symposium on VLSI 2016: 269-274 - [c9]Mohsen Imani, Yeseong Kim, Abbas Rahimi, Tajana Rosing:
ACAM: Approximate Computing Based on Adaptive Associative Memory with Online Learning. ISLPED 2016: 162-167 - [c8]Mohsen Imani, Shruti Patil, Tajana Simunic Rosing:
Low power data-aware STT-RAM based hybrid cache architecture. ISQED 2016: 88-94 - [c7]Mohsen Imani, Pietro Mercati, Tajana Rosing:
ReMAM: Low energy Resistive Multi-stage Associative Memory for energy efficient computing. ISQED 2016: 101-106 - [c6]Mohsen Imani, Yan Cheng, Tajana Rosing:
Processing Acceleration with Resistive Memory-based Computation. MEMSYS 2016: 208-210 - [c5]Mohsen Imani, Abbas Rahimi, Yeseong Kim, Tajana Rosing:
A low-power hybrid magnetic cache architecture exploiting narrow-width values. NVMSA 2016: 1-6 - [i2]Mohsen Imani, Mehrdad Amirabadi, Matthew Wright:
Modified Relay Selection and Circuit Selection for Faster Tor. CoRR abs/1608.07343 (2016) - 2015
- [c4]Yeseong Kim, Mohsen Imani, Shruti Patil, Tajana Simunic Rosing:
CAUSE: Critical Application Usage-Aware Memory System using Non-volatile Memory for Mobile Devices. ICCAD 2015: 690-696 - [c3]Mohsen Imani, Shruti Patil, Tajana Simunic Rosing:
Hierarchical design of robust and low data dependent FinFET based SRAM array. NANOARCH 2015: 63-68 - [i1]Marc Juárez, Mohsen Imani, Mike Perry, Claudia Díaz, Matthew Wright:
WTF-PAD: Toward an Efficient Website Fingerprinting Defense for Tor. CoRR abs/1512.00524 (2015) - 2013
- [c2]Mohsen Jafari, Mohsen Imani, Mohammad Ansari, Morteza Fathipour, Nader Sehatbakhsh:
Design of an ultra-low power 32-bit adder operating at subthreshold voltages in 45-nm FinFET. DTIS 2013: 167-168 - [c1]Mohsen Jafari, Mohsen Imani, Morteza Fathipour, Nader Sehatbakhsh:
Bottom-up design of a high performance ultra-low power DFT utilizing multiple-VDD, multiple-Vth and gate sizing. DTIS 2013: 178-179
Coauthor Index
aka: Tajana Simunic Rosing

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