Memory latency and bandwidth are significant bottlenecks in designing in-memory indexes.
Processing-in-memory (PIM), an emerging hardware design approach, alleviates this …

Data movement between memory and processors is a major bottleneck in modern
computing systems. The processing-in-memory (PIM) paradigm aims to alleviate this …

RNA sequence quantification is an important analysis method to measure transcript
abundances. A key overhead in RNA-seq quantification is to map a set of RNA reads to …

Due to the separate memory and computation units in traditional Von-Neumann architecture,
massive data transfer dominates the overall computing system's power and latency, known …

This work presents the first resistive random access memory (RRAM)-based compute-in-
memory (CIM) macro design tailored for genome processing. We analyze and demonstrate …

Today's computing systems require moving data back-and-forth between computing
resources (eg, CPUs, GPUs, accelerators) and off-chip main memory so that computation …

In this work, we present an efficient Processing in MRAM-Accelerated De Bruijn Graph-
based DNA Assembly platform, named PANDA, based on an optimized and hardware …

Processing-in-memory (PIM) architecture is promising for accelerating deep neural network
(DNN) training due to its low-latency and energy-efficient data movement between …

The growth in speed and density of programmable logic devices, such as Field
programmable gate arrays (FPGA), enables sophisticated designs to be created within a …