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 …
Rethinking software runtimes for disaggregated memory
Disaggregated memory can address resource provisioning inefficiencies in current
datacenters. Multiple software runtimes for disaggregated memory have been proposed in …
datacenters. Multiple software runtimes for disaggregated memory have been proposed in …
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 …
Syncron: Efficient synchronization support for near-data-processing architectures
C Giannoula, N Vijaykumar… - … Symposium on High …, 2021 - ieeexplore.ieee.org
Near-Data-Processing (NDP) architectures present a promising way to alleviate data
movement costs and can provide significant performance and energy benefits to parallel …
movement costs and can provide significant performance and energy benefits to parallel …
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 …
NATSA: a near-data processing accelerator for time series analysis
Time series analysis is a key technique for extracting and predicting events in domains as
diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and …
diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and …
Benchmarking memory-centric computing systems: Analysis of real processing-in-memory hardware
Many modern workloads such as neural network inference and graph processing are
fundamentally memory-bound. For such workloads, data movement between memory and …
fundamentally memory-bound. For such workloads, data movement between memory and …