[HTML][HTML] From molecules to genomic variations: Accelerating genome analysis via intelligent algorithms and architectures
We now need more than ever to make genome analysis more intelligent. We need to read,
analyze, and interpret our genomes not only quickly, but also accurately and efficiently …
analyze, and interpret our genomes not only quickly, but also accurately and efficiently …
A modern primer on processing in memory
Modern computing systems are overwhelmingly designed to move data to computation. This
design choice goes directly against at least three key trends in computing that cause …
design choice goes directly against at least three key trends in computing that cause …
Benchmarking a new paradigm: Experimental analysis and characterization of a real processing-in-memory system
Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …
fundamentally memory-bound. For such workloads, the data movement between main …
SIMDRAM: A framework for bit-serial SIMD processing using DRAM
Processing-using-DRAM has been proposed for a limited set of basic operations (ie, logic
operations, addition). However, in order to enable full adoption of processing-using-DRAM …
operations, addition). However, in order to enable full adoption of processing-using-DRAM …
Resource-efficient convolutional networks: A survey on model-, arithmetic-, and implementation-level techniques
Convolutional neural networks (CNNs) are used in our daily life, including self-driving cars,
virtual assistants, social network services, healthcare services, and face recognition, among …
virtual assistants, social network services, healthcare services, and face recognition, among …
Sisa: Set-centric instruction set architecture for graph mining on processing-in-memory systems
Simple graph algorithms such as PageRank have been the target of numerous hardware
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …
DAMOV: A new methodology and benchmark suite for evaluating data movement bottlenecks
Data movement between the CPU and main memory is a first-order obstacle against improv
ing performance, scalability, and energy efficiency in modern systems. Computer systems …
ing performance, scalability, and energy efficiency in modern systems. Computer systems …
FPGA-based near-memory acceleration of modern data-intensive applications
Modern data-intensive applications demand high computational capabilities with strict
power constraints. Unfortunately, such applications suffer from a significant waste of both …
power constraints. Unfortunately, such applications suffer from a significant waste of both …
Benchmarking a new paradigm: An experimental analysis of a real processing-in-memory architecture
Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …
fundamentally memory-bound. For such workloads, the data movement between main …
QUAC-TRNG: High-throughput true random number generation using quadruple row activation in commodity DRAM chips
True random number generators (TRNG) sample random physical processes to create large
amounts of random numbers for various use cases, including security-critical cryptographic …
amounts of random numbers for various use cases, including security-critical cryptographic …