Memristive logic: A framework for evaluation and comparison. - John Reuben; Rotem Ben Hur; Nimrod Wald; Nishil Talati; Ameer Haj Ali; Pierre-Emmanuel Gaillardon; Shahar Kvatinsky (PATMOS, 2017)

Practical challenges in delivering the promises of real processing-in-memory machines. - Nishil Talati; Ameer Haj Ali; Rotem Ben Hur; Nimrod Wald; Ronny Ronen; Pierre-Emmanuel Gaillardon; Shahar Kvatinsky (DATE, 2018)

Efficient Algorithms for In-Memory Fixed Point Multiplication Using MAGIC. - Ameer Haj Ali; Rotem Ben Hur; Nimrod Wald; Shahar Kvatinsky (ISCAS, 2018)

Not in Name Alone: A Memristive Memory Processing Unit for Real In-Memory Processing. - Ameer Haj Ali; Rotem Ben Hur; Nimrod Wald; Ronny Ronen; Shahar Kvatinsky (IEEE Micro, 2018)

IMAGING: In-Memory AlGorithms for Image processiNG. - Ameer Haj Ali; Rotem Ben Hur; Nimrod Wald; Ronny Ronen; Shahar Kvatinsky (IEEE Trans. Circuits Syst. I Regul. Pap., 2018)

A Taxonomy and Evaluation Framework for Memristive Logic. - John Reuben; Nishil Talati; Nimrod Wald; Rotem Ben Hur; Ameer Haj Ali; Pierre-Emmanuel Gaillardon; Shahar Kvatinsky (Handbook of Memristor Networks, 2019)

AutoPhase: Compiler Phase-Ordering for HLS with Deep Reinforcement Learning. - Qijing Huang 001; Ameer Haj-Ali; William S. Moses; John Xiang; Ion Stoica; Krste Asanovic; John Wawrzynek (FCCM, 2019)

AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning. - Ameer Haj Ali; Qijing Huang 001; William S. Moses; John Xiang; Ion Stoica; Krste Asanovic; John Wawrzynek (CoRR, 2019)

Deep Reinforcement Learning in System Optimization. - Ameer Haj-Ali; Nesreen K. Ahmed; Theodore L. Willke; Joseph Gonzalez 001; Krste Asanovic; Ion Stoica (CoRR, 2019)

Gemmini: An Agile Systolic Array Generator Enabling Systematic Evaluations of Deep-Learning Architectures. - Hasan Genc; Ameer Haj-Ali; Vighnesh Iyer; Alon Amid; Howard Mao; John Charles Wright; Colin Schmidt 001; Jerry Zhao; Albert J. Ou; Max Banister; Yakun Sophia Shao; Borivoje Nikolic; et al. (CoRR, 2019)

Supporting the Momentum Training Algorithm Using a Memristor-Based Synapse. - Tzofnat Greenberg-Toledo; Roee Mazor; Ameer Haj Ali; Shahar Kvatinsky (IEEE Trans. Circuits Syst. I Regul. Pap., 2019)

NeuroVectorizer: end-to-end vectorization with deep reinforcement learning. - Ameer Haj-Ali; Nesreen K. Ahmed; Theodore L. Willke; Yakun Sophia Shao; Krste Asanovic; Ion Stoica (CGO, 2020)

AutoCkt: Deep Reinforcement Learning of Analog Circuit Designs. - Keertana Settaluri; Ameer Haj-Ali; Qijing Huang 001; Kourosh Hakhamaneshi; Borivoje Nikolic (DATE, 2020)

AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning. - Ameer Haj-Ali; Qijing (Jenny) Huang; William S. Moses; John Xiang; Krste Asanovic; John Wawrzynek; Ion Stoica (MLSys, 2020)

RLDRM: Closed Loop Dynamic Cache Allocation with Deep Reinforcement Learning for Network Function Virtualization. - Bin Li 018; Yipeng Wang 002; Ren Wang 001; Charlie Tai; Ravi R. Iyer 001; Zhu Zhou; Andrew Herdrich; Tong Zhang; Ameer Haj-Ali; Ion Stoica; Krste Asanovic (NetSoft, 2020)

Ansor: Generating High-Performance Tensor Programs for Deep Learning. - Lianmin Zheng; Chengfan Jia; Minmin Sun; Zhao Wu; Cody Hao Yu; Ameer Haj-Ali; Yida Wang 003; Jun Yang; Danyang Zhuo; Koushik Sen; Joseph E. Gonzalez; Ion Stoica (OSDI, 2020)

ProTuner: Tuning Programs with Monte Carlo Tree Search. - Ameer Haj-Ali; Hasan Genc; Qijing Huang 001; William S. Moses; John Wawrzynek; Krste Asanovic; Ion Stoica (CoRR, 2020)

SIMPLER MAGIC: Synthesis and Mapping of In-Memory Logic Executed in a Single Row to Improve Throughput. - Rotem Ben Hur; Ronny Ronen; Ameer Haj Ali; Debjyoti Bhattacharjee; Adi Eliahu; Natan Peled; Shahar Kvatinsky (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Machine Learning in Compiler Optimization. - Ameer Haj-Ali (2020)

Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration. - Hasan Genc; Seah Kim; Alon Amid; Ameer Haj-Ali; Vighnesh Iyer; Pranav Prakash; Jerry Zhao; Daniel Grubb; Harrison Liew; Howard Mao; Albert J. Ou; Colin Schmidt 001; et al. (DAC, 2021)

TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers. - Lianmin Zheng; Ruochen Liu; Junru Shao; Tianqi Chen 001; Joseph Gonzalez 001; Ion Stoica; Ameer Haj-Ali (NeurIPS Datasets and Benchmarks, 2021)