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The energy consumption of DRAM is a critical concern in modern computing systems. Improvements in manufacturing process technology have allowed DRAM vendors to lower the DRAM supply voltage conservatively, which reduces some of the DRAM…

This article summarizes key results of our work on experimental characterization and analysis of latency variation and latency-reliability trade-offs in modern DRAM chips, which was published in SIGMETRICS 2016, and examines the work's…

Variation has been shown to exist across the cells within a modern DRAM chip. We empirically demonstrate a new form of variation that exists within a real DRAM chip, induced by the design and placement of different components in the DRAM…

In modern systems, DRAM-based main memory is significantly slower than the processor. Consequently, processors spend a long time waiting to access data from main memory, making the long main memory access latency one of the most critical…

Hardware Architecture · Computer Science 2016-11-01 Donghyuk Lee

Over the past two decades, the storage capacity and access bandwidth of main memory have improved tremendously, by 128x and 20x, respectively. These improvements are mainly due to the continuous technology scaling of DRAM (dynamic…

Hardware Architecture · Computer Science 2017-12-25 Kevin K. Chang

This paper summarizes the idea of Adaptive-Latency DRAM (AL-DRAM), which was published in HPCA 2015, and examines the work's significance and future potential. AL-DRAM is a mechanism that optimizes DRAM latency based on the DRAM module and…

Hardware Architecture · Computer Science 2018-05-09 Donghyuk Lee , Yoongu Kim , Gennady Pekhimenko , Samira Khan , Vivek Seshadri , Kevin Chang , Onur Mutlu

Dynamic Random Access Memory (DRAM) is the de-facto choice for main memory devices due to its cost-effectiveness. It offers a larger capacity and higher bandwidth compared to SRAM but is slower than the latter. With each passing generation,…

Hardware Architecture · Computer Science 2022-01-19 Kaustav Goswami , Hemanta Kumar Mondal , Shirshendu Das , Dip Sankar Banerjee

This paper summarizes the idea of Adaptive-Latency DRAM (AL-DRAM), which was published in HPCA 2015. The key goal of AL-DRAM is to exploit the extra margin that is built into the DRAM timing parameters to reduce DRAM latency. The key…

Hardware Architecture · Computer Science 2016-03-29 Donghyuk Lee , Yoongu Kim , Gennady Pekhimenko , Samira Khan , Vivek Seshadri , Kevin Chang , Onur Mutlu

This dissertation rigorously characterizes many modern commodity DRAM devices and shows that by exploiting DRAM access timing margins within manufacturer-recommended DRAM timing specifications, we can significantly improve system…

Hardware Architecture · Computer Science 2021-09-30 Jeremie S. Kim

Modern computing devices employ High-Bandwidth Memory (HBM) to meet their memory bandwidth requirements. An HBM-enabled device consists of multiple DRAM layers stacked on top of one another next to a compute chip (e.g. CPU, GPU, and FPGA)…

Hardware Architecture · Computer Science 2021-01-05 Seyed Saber Nabavi Larimi , Behzad Salami , Osman S. Unsal , Adrian Cristal Kestelman , Hamid Sarbazi-Azad , Onur Mutlu

Our ISCA 2013 paper provides a fundamental empirical understanding of two major factors that make it very difficult to determine the minimum data retention time of a DRAM cell, based on the first comprehensive experimental characterization…

Hardware Architecture · Computer Science 2023-06-29 Onur Mutlu

We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate…

Main memory (DRAM) consumes as much as half of the total system power in a computer today, resulting in a growing need to develop new DRAM architectures and systems that consume less power. Researchers have long relied on DRAM power models…

Modern large-scale computing systems (data centers, supercomputers, cloud and edge setups and high-end cyber-physical systems) employ heterogeneous architectures that consist of multicore CPUs, general-purpose many-core GPUs, and…

Data center loads have expanded significantly in recent years. Compared to traditional loads, data centers are highly sensitive to voltage deviations and thus their protection mechanisms trip more proactively during voltage fluctuations.…

Systems and Control · Electrical Eng. & Systems 2025-10-07 Yiheng Xie , Wenqi Cui , Adam Wierman

On-chip memory (usually based on Static RAMs-SRAMs) are crucial components for various computing devices including heterogeneous devices, e.g., GPUs, FPGAs, ASICs to achieve high performance. Modern workloads such as Deep Neural Networks…

Hardware Architecture · Computer Science 2022-07-20 İsmail Emir Yüksel , Behzad Salami , Oğuz Ergin , Osman Sabri Ünsal , Adrian Cristal Kestelman

It has become increasingly difficult to understand the complex interaction between modern applications and main memory, composed of DRAM chips. Manufacturers are now selling and proposing many different types of DRAM, with each DRAM type…

Hardware Architecture · Computer Science 2019-10-21 Saugata Ghose , Tianshi Li , Nastaran Hajinazar , Damla Senol Cali , Onur Mutlu

This paper summarizes the idea of Tiered-Latency DRAM (TL-DRAM), which was published in HPCA 2013, and examines the work's significance and future potential. The capacity and cost-per-bit of DRAM have historically scaled to satisfy the…

Hardware Architecture · Computer Science 2018-05-09 Donghyuk Lee , Yoongu Kim , Vivek Seshadri , Jamie Liu , Lavanya Subramanian , Onur Mutlu

Modern DRAM chips are subject to read disturbance errors. State-of-the-art read disturbance mitigations rely on accurate and exhaustive characterization of the read disturbance threshold (RDT) (e.g., the number of aggressor row activations…

Because deep neural networks (DNNs) rely on a large number of parameters and computations, their implementation in energy-constrained systems is challenging. In this paper, we investigate the solution of reducing the supply voltage of the…

Machine Learning · Computer Science 2019-11-26 Ghouthi Boukli Hacene , François Leduc-Primeau , Amal Ben Soussia , Vincent Gripon , François Gagnon
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