no code implementations • 6 Sep 2021 • Zixuan Jiang, Ebrahim Songhori, Shen Wang, Anna Goldie, Azalia Mirhoseini, Joe Jiang, Young-Joon Lee, David Z. Pan
In physical design, human designers typically place macros via trial and error, which is a Markov decision process.
no code implementations • 26 May 2021 • Dan Zhang, Safeen Huda, Ebrahim Songhori, Kartik Prabhu, Quoc Le, Anna Goldie, Azalia Mirhoseini
The rapidly-changing deep learning landscape presents a unique opportunity for building inference accelerators optimized for specific datacenter-scale workloads.
2 code implementations • 22 Apr 2020 • Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Jiang, Ebrahim Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Sungmin Bae, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Anand Babu, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean
To achieve these results, we pose placement as a Reinforcement Learning (RL) problem and train an agent to place the nodes of a chip netlist onto a chip canvas.
no code implementations • ICLR 2020 • Amir Yazdanbakhsh, Ebrahim Songhori, Robert Ormandi, Anna Goldie, Azalia Mirhoseini
In our experiments, we use PPO as our baseline policy optimization algorithm.
no code implementations • 25 Sep 2019 • Jialin Song, Joe Wenjie Jiang, Amir Yazdanbakhsh, Ebrahim Songhori, Anna Goldie, Navdeep Jaitly, Azalia Mirhoseini
On the other end of the spectrum, approaches rooted in Policy Iteration, such as Dual Policy Iteration do not choose next step actions based on an expert, but instead use planning or search over the policy to choose an action distribution to train towards.