Deep Neural Networks (DNNs) are the algorithm of choice for image processing applications. DNNs present highly parallel workloads that lead to the emergence of custom hardware accelerators. Deep Learning (DL) models specialized in different tasks ...

Emerging Non-Volatile Memory (NVM) technologies offer high capacity and energy efficiency compared to DRAM, but suffer from limited write endurance and longer latencies. Prior work seeks the best of both technologies by combining DRAM and NVM in hybrid ...

Industry is increasingly turning to reconfigurable architectures like FPGAs and CGRAs for improved performance and energy efficiency. Unfortunately, adoption of these architectures has been limited by their programming models. HDLs lack abstractions for ...

Fast, byte-addressable non-volatile memory (NVM) embraces both near-DRAM latency and disk-like persistence, which has generated considerable interests to revolutionize system software stack and programming models. However, it is less understood how NVM ...

Accelerators are increasingly recognized as one of the major drivers of future computational growth. For accelerators, shared virtual memory (VM) promises to simplify programming and provide safe data sharing with CPUs. Unfortunately, the overheads of ...

Deep neural networks (DNN) have demonstrated highly promising results across computer vision and speech recognition, and are becoming foundational for ubiquitous AI. The computational complexity of these algorithms and a need for high energy-efficiency ...

Recent developments in Non-Volatile Memories (NVMs) have opened up a new horizon for in-memory computing. Despite the significant performance gain offered by computational NVMs, previous works have relied on manual mapping of specialized kernels to the ...

With the recent trend of promoting Field-Programmable Gate Arrays (FPGAs) to first-class citizens in accelerating compute-intensive applications in networking, cloud services and artificial intelligence, FPGAs face two major challenges in sustaining ...

We present a library in Haskell for programming Field Programmable Gate Arrays (FPGAs), including hardware software co-design. Code for software (in C) and hardware (in VHDL) is generated from a single program, along with the code to support ...

Software-Defined Networking (SDN) allows controlling applications to install fine-grained forwarding policies in the underlying switches. Ternary Content Addressable Memory (TCAM) enables fast lookups in hardware switches with flexible wildcard rule ...

Convolutional neural networks (CNNs) are widely adopted in artificial intelligent systems. In contrast to conventional computing centric applications, the computational and memory resources of CNN applications are mixed together in the network weights. ...

With the recent advance of wearable devices and Internet of Things (IoTs), it becomes attractive to implement the Deep Convolutional Neural Networks (DCNNs) in embedded and portable systems. Currently, executing the software-based DCNNs requires high-...

The slotted-page structure is a database page format commonly used for managing variable-length records. In this work, we develop a novel "failure-atomic slotted page structure" for persistent memory that leverages byte addressability and durability of ...

With Solid State Disks (SSDs) offering high degrees of parallelism, SSD controllers place data and direct requests to exploit the maximum offered hardware parallelism. In the quest to maximize parallelism and utilization, sub-requests of a request that ...

Specialized hardware accelerators have performance and energy-efficiency advantages over general-purpose processors. To fully realize these benefits and aid programmability, accelerators may share a physical and virtual address space and full cache ...

Shared caches are generally optimized to maximize the overall throughput, fairness, or both, among multiple competing programs. In shared environments and compute clouds, users are often unrelated to each other. In such circumstances, an overall gain ...

In recent years the computing landscape has seen an increasing shift towards specialized accelerators. Field programmable gate arrays (FPGAs) are particularly promising for the implementation of these accelerators, as they offer significant performance ...

Emerging byte-addressable non-volatile memory is considered an alternative storage device for database logs that require persistency and high performance. In this work, we develop NVWAL (NVRAM Write-Ahead Logging) for SQLite. The contribution of NVWAL ...

Ensuring the integrity and security of the memory system is critical. Recent studies have shown serious security concerns due to "rowhammer" attacks, where repeated accesses to a row of memory cause bit flips in adjacent rows. Recent work by Google's ...

Modern warehouse-scale computers (WSCs) are being outfitted with accelerators to provide the significant compute required by emerging intelligent personal assistant (IPA) workloads such as voice recognition, image classification, and natural language ...