81 citations · 98 across the 7 of their papers we have counts for
8 papers
Swordfish: A Framework for Evaluating Deep Neural Network-based Basecalling using Computation-In-Memory with Non-Ideal Memristors
Taha Shahroodi, Gagandeep Singh, Mahdi Zahedi +6
Basecalling, an essential step in many genome analysis studies, relies on large Deep Neural Networks (DNNs) to achieve high accuracy. Unfortunately, these DNNs are computationally…
BCIM: Efficient Implementation of Binary Neural Network Based on Computation in Memory
Mahdi Zahedi, Taha Shahroodi, Stephan Wong +1
Applications of Binary Neural Networks (BNNs) are promising for embedded systems with hard constraints on computing power. Contrary to conventional neural networks with the floatin…
A Case for Transparent Reliability in DRAM Systems
Minesh Patel, Taha Shahroodi, Aditya Manglik +4
Today's systems have diverse needs that are difficult to address using one-size-fits-all commodity DRAM. Unfortunately, although system designers can theoretically adapt commodity…
BurstLink: Techniques for Energy-Efficient Conventional and Virtual Reality Video Display
Jawad Haj-Yahya, Jisung Park, Rahul Bera +5
Conventional planar video streaming is the most popular application in mobile systems and the rapid growth of 360 video content and virtual reality (VR) devices are accelerating th…
Bit-Exact ECC Recovery (BEER): Determining DRAM On-Die ECC Functions by Exploiting DRAM Data Retention Characteristics
Minesh Patel, Jeremie S. Kim, Taha Shahroodi +2
Increasing single-cell DRAM error rates have pushed DRAM manufacturers to adopt on-die error-correction coding (ECC), which operates entirely within a DRAM chip to improve factory…
CLR-DRAM: A Low-Cost DRAM Architecture Enabling Dynamic Capacity-Latency Trade-Off
Haocong Luo, Taha Shahroodi, Hasan Hassan +5
DRAM is the prevalent main memory technology, but its long access latency can limit the performance of many workloads. Although prior works provide DRAM designs that reduce DRAM ac…