PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAM
Commodity DRAM-based processing-using-memory (PuM) techniques that are supported
by off-the-shelf DRAM chips present an opportunity for alleviating the data movement …
by off-the-shelf DRAM chips present an opportunity for alleviating the data movement …
DRAM bender: An extensible and versatile FPGA-based infrastructure to easily test state-of-the-art DRAM chips
To understand and improve DRAM performance, reliability, security, and energy efficiency,
prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art …
prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art …
Recryptor: A reconfigurable cryptographic cortex-M0 processor with in-memory and near-memory computing for IoT security
Providing security for the Internet of Things (IoT) is increasingly important, but supporting
many different cryptographic algorithms and standards within the physical constraints of IoT …
many different cryptographic algorithms and standards within the physical constraints of IoT …
Evaluating machine learningworkloads on memory-centric computing systems
Training machine learning (ML) algorithms is a computationally intensive process, which is
frequently memory-bound due to repeatedly accessing large training datasets. As a result …
frequently memory-bound due to repeatedly accessing large training datasets. As a result …
BLADE: An in-cache computing architecture for edge devices
Area and power-constrained edge devices are increasingly utilized to perform compute
intensive workloads, necessitating increasingly area and power-efficient accelerators. In this …
intensive workloads, necessitating increasingly area and power-efficient accelerators. In this …
Analysis and optimization of the memory hierarchy for graph processing workloads
Graph processing is an important analysis technique for a wide range of big data
applications. The ability to explicitly represent relationships between entities gives graph …
applications. The ability to explicitly represent relationships between entities gives graph …
Transpimlib: Efficient transcendental functions for processing-in-memory systems
GF Oliveira, J Gómez-Luna… - … Analysis of Systems …, 2023 - ieeexplore.ieee.org
Processing-in-memory (PIM) promises to alleviate the data movement bottleneck in modern
computing systems. However, current real-world PIM systems have the inherent …
computing systems. However, current real-world PIM systems have the inherent …
Casper: Accelerating stencil computations using near-cache processing
Stencil computations are commonly used in a wide variety of scientific applications, ranging
from large-scale weather prediction to solving partial differential equations. Stencil …
from large-scale weather prediction to solving partial differential equations. Stencil …
Graphide: A graph processing accelerator leveraging in-dram-computing
In this paper, we propose GraphiDe, a novel DRAM-based processing-in-memory (PIM)
accelerator for graph processing. It transforms current DRAM architecture to massively …
accelerator for graph processing. It transforms current DRAM architecture to massively …
A 4 + 2T SRAM for Searching and In-Memory Computing With 0.3-V
This paper presents a 4+ 2T SRAM for embedded searching and in-memory-computing
applications. The proposed SRAM cell uses the n-well as the write wordline to perform write …
applications. The proposed SRAM cell uses the n-well as the write wordline to perform write …