BuMP: Bulk Memory Access Prediction and Streaming

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Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher pow ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query ...

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Gain-cell embedded DRAM (GC-eDRAM) is a high-density logic-compatible alternative to conventional static random-access memory (SRAM) and embedded DRAM (eDRAM). However, GC-eDRAM suffers from a reduced data retention time (DRT) at deeply-scaled process node ...

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

Owing to the advancements in the area of power electronics, efficient and flexible ac to dc conversion is made possible, bringing back into focus the idea of the dc power transmission at various voltage levels. Several technical and economical factors advo ...

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database opera ...

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the h ...

BuMP: Bulk Memory Access Prediction and Streaming

Chattez avec Graph Search

EdgeAI-Aware Design of In-Memory Computing Architectures

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Secure Interface Design Leveraging Hardware/Software Support

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Is the powersave governor really saving power?

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Rebooting Virtual Memory with Midgard

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

HPCache: memory-efficient OLAP through proportional caching revisited

How to Achieve Large-Area Ultra-Fast Operation of MoS 2 Monolayer Flash Memories?

Chaosity: Understanding Contemporary NUMA-architectures

A 128-kbit GC-eDRAM With Negative Boosted Bootstrap Driver for 11.3x Lower-Refresh Frequency at a 2.5% Area Overhead in 28-nm FD-SOI

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

On Energy Control of Modular Multilevel Converters

uKharon: A Membership Service for Microsecond Applications

Determining an optimum quantity of interleaved instruction streams of defined coroutines

Engram cell connectivity as a mechanism for information encoding and memory function