RowHammer (RH) is a significant and worsening security, safety, and
reli...
The performance and capacity of solid-state drives (SSDs) are continuous...
Processing-in-memory (PIM) promises to alleviate the data movement bottl...
Fast and accurate climate simulations and weather predictions are critic...
Agent-based modeling plays an essential role in gaining insights into
bi...
Partitioning applications between NDP and host CPU cores causes inter-se...
Time Series Analysis (TSA) is a critical workload for consumer-facing
de...
Recent nano-technological advances enable the Monolithic 3D (M3D) integr...
Neural networks (NNs) are growing in importance and complexity. A neural...
Bulk bitwise operations, i.e., bitwise operations on large bit vectors, ...
Machine learning has recently gained traction as a way to overcome the s...
Motivation: Pairwise sequence alignment is a very time-consuming step in...
Sequence alignment is a fundamentally memory bound computation whose
per...
Profile hidden Markov models (pHMMs) are widely used in many bioinformat...
Training machine learning (ML) algorithms is a computationally intensive...
Training machine learning algorithms is a computationally intensive proc...
Time series analysis is a key technique for extracting and predicting ev...
DRAM-based main memory is used in nearly all computing systems as a majo...
Today's computing systems require moving data back-and-forth between
com...
The increasing prevalence and growing size of data in modern application...
We now need more than ever to make genome analysis more intelligent. We ...
Hybrid storage systems (HSS) use multiple different storage devices to
p...
A critical step of genome sequence analysis is the mapping of sequenced ...
We show that the wavefront algorithm can achieve higher pairwise read
al...
Several manufacturers have already started to commercialize near-bank
Pr...
We improve on GenASM, a recent algorithm for genomic sequence alignment,...
Dilated and transposed convolutions are widely used in modern convolutio...
Several manufacturers have already started to commercialize near-bank
Pr...
Dynamic parallelism on GPUs allows GPU threads to dynamically launch oth...
Stencil computation is one of the most used kernels in a wide variety of...
The number and diversity of consumer devices are growing rapidly, alongs...
Processing-using-memory (PuM) techniques leverage the analog operation o...
Many modern workloads such as neural network inference and graph process...
Ongoing climate change calls for fast and accurate weather and climate
m...
Modern data-intensive applications demand high computation capabilities ...
DRAM is the dominant main memory technology used in modern computing sys...
To operate efficiently across a wide range of workloads with varying pow...
Processing-using-DRAM has been proposed for a limited set of basic opera...
Many modern workloads, such as neural networks, databases, and graph
pro...
Data movement between the CPU and main memory is a first-order obstacle
...
Data movement between main memory and the processor is a significant
con...
Simple graph algorithms such as PageRank have been the target of numerou...
Conventional planar video streaming is the most popular application in m...
Near-Data-Processing (NDP) architectures present a promising way to alle...
Processing-using-DRAM has been proposed for a limited set of basic opera...
Modern computing systems are overwhelmingly designed to move data to
com...
Time series analysis is a key technique for extracting and predicting ev...
Sparse general matrix-matrix multiplication (spGEMM) is an essential
com...
DRAM Main memory is a performance bottleneck for many applications due t...
Ongoing climate change calls for fast and accurate weather and climate
m...