Nikil Dutt

Nikil Dutt
University of California, Irvine | UCI · Department of Computer Science

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656
Publications
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Introduction
Skills and Expertise

Publications

Publications (656)
Article
Deep-learning-based intelligent services have become prevalent in cyber-physical applications including smart cities and health-care. Deploying deep-learning-based intelligence near the end-user enhances privacy protection, responsiveness, and reliability. Resource-constrained end-devices must be carefully managed in order to meet the latency and e...
Article
Full-text available
Modern heterogeneous CPU-GPU-based mobile architectures, which execute intensive mobile gaming/graphics applications, use software governors to achieve high performance with energy-efficiency. However, existing governors typically utilize simple statistical or heuristic models, assuming linear relationships using a small unbalanced dataset of mobil...
Article
Full-text available
Recent advances in pervasive Internet of Things (IoT) technologies and edge computing have opened new avenues for development of ubiquitous health monitoring applications. Delivering an acceptable level of usability and accuracy for these healthcare IoT applications requires optimization of both system-driven and data-driven aspects which are typic...
Conference Paper
Full-text available
Quantum computers promise to solve hard mathematical problems such as integer factorization and discrete logarithms in polynomial time, making standardized public-key cryptography (such as digital signature and key agreement) insecure. Lattice-Based Cryptography (LBC) is a promising post-quantum public key cryptographic protocol that could replace...
Article
Full-text available
Monitoring people's stress levels has become an essential part of behavioral studies for physical and mental illnesses conducted within the biopsychosocial framework. There have been several stress assessment studies in laboratory-based controlled settings. However, the results of these studies do not always translate effectively to an everyday con...
Conference Paper
Full-text available
Traumatic Brain Injury (TBI) is highly prevalent, affecting ~1% of the U.S. population, with lifetime economic costs estimated to be over $75 billion. In the U.S., there are about 50,000 deaths annually related to TBI, and many others are permanently disabled. However, it is currently unknown which individuals will develop persistent disability fol...
Article
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Many data-driven applications including computer vision, machine learning, speech recognition, and medical di-agnostics show tolerance to computation error. These applications are often accelerated on GPUs, but the performance improvements require high energy usage. In this paper, we present DRAAW, an approximate computing technique capable of acce...
Book
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In this chapter, we explore adaptive resource management techniques for cyber-physical systems-on-chip that employ principles of computational self-awareness to varying degrees, specifically reflection. By supporting various self-X properties, systems gain the ability to reason about runtime configuration decisions by considering the significance o...
Book
Full-text available
Due to the consistent pressing quest of larger on-chip memories and caches of multicore and manycore architectures, Spin Transfer Torque Magnetic RAM (STT-MRAM or STT-RAM) has been proposed as a promising technology to replace classical SRAMs in near-future devices. Main advantages of STT-RAMs are a considerably higher transistor density and a negl...
Conference Paper
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MPSoCs increasingly depend on adaptive resource management strategies at runtime for efficient utilization of resources when executing complex application workloads. In particular, conflicting demands for adequate computation performance and power-/energy-efficiency constraints make desired application goals hard to achieve. We present a hierarchic...
Article
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The advent of the quantum computer makes current public-key infrastructure insecure. Cryptography community is addressing this problem by designing, efficiently implementing, and evaluating novel public-key algorithms capable of withstanding quantum computational power. Governmental agencies, such as NIST, are promoting standardization of quantum-r...
Conference Paper
This paper explores the challenges of HCI work within multidisciplinary research projects across health sciences, social sciences, and engineering, through discussion of a specific case study research project focused on supporting under-resourced pregnant women. Capturing the perspectives of community-based health care workers (N=14) using wearable...
Conference Paper
Resource management strategies for many-core systems dictate the sharing of resources among applications such as power, processing cores, and memory bandwidth in order to achieve system goals. System goals require consideration of both system constraints (e.g., power envelope) and user demands (e.g., response time, energy-efficiency). Existing appr...
Article
Memory approximation enables trading off quality/accuracy for performance or energy gains. Traditionally, application programmers are burdened with the difficult task of setting memory approximation knobs to achieve the desired quality of service (QoS). Our self-adaptive approach for memory approximation eases the programmer’s burden: simply specif...
Article
Sleep is a composite of physiological and behavioral processes that undergo substantial changes during and after pregnancy. These changes might lead to sleep disorders and adverse pregnancy outcomes. Several studies have investigated this issue; however, they were restricted to subjective measurements or short-term actigraphy methods. This is insuf...
Conference Paper
Full-text available
In the era of Fog computing where one can decide to compute certain time-critical tasks at the edge of the network, designers often encounter a question whether the sensor layer provides the optimal response time for a service, or the Fog layer, or their combination. In this context, minimizing the total response time using computation migration is...
Conference Paper
Management of energy dissipation and battery life is a challenge in health monitoring wearables. Low-quality data collection, non-reliable monitoring process, and missing important health events are consequences of single-goal fixed-policy solutions. In this research, energy dissipation of IoT-based wearable systems is managed through a dynamic mul...
Conference Paper
Full-text available
Run-time resource allocation of heterogeneous multi-core systems is challenging with varying workloads and limited power and energy budgets. User interaction within these systems changes the performance requirements, often conflicting with concurrent applications' objective and system constraints. Current resource allocation approaches focus on opt...
Article
The typical workload of many-core systems produces peaks and valleys of resources utilization throughout the time. The power capping limits the full system utilization in a workload peak, but also creates a power slack to apply different resource management (RM) policy in a valley phase. Related works do not consider this workload behavior, by prop...
Conference Paper
High abstraction level models can be used within the system-level simulation to allow rapid evaluations of architectural aspects in early Design Space Exploration (DSE) and direct the development decisions. Further, early DSE is of paramount importance in the specification of future Embedded Systems (ES) and its evaluation for applications with hig...
Conference Paper
Full-text available
Abstract—Studies have shown memory needs vary significantly across applications. Recent work has explored using hybridmemory technology (SRAM+NVM) in on-chip memories of mul-ticore processors (CMPs) to support the varied needs of diverse workloads. Such works suggest architectural modifications that require supplemental management in the memory hie...
Conference Paper
Studies have shown memory needs vary significantly across applications. Recent work has explored using hybrid memory technology (SRAM+NVM) in on-chip memories of mul-ticore processors (CMPs) to support the varied needs of diverse workloads. Such works suggest architectural modifications that require supplemental management in the memory hierarchy....
Conference Paper
Run-time resource management of heterogeneous multi-core systems is challenging due to i) dynamic workloads, that often result in ii) conflicting knob actuation decisions, which potentially iii) compromise on performance for thermal safety. We present a runtime resource management strategy for performance guarantees under power constraints using fu...
Conference Paper
Virtual machines (VMs) are being deployed on embedded systems to integrate multiple applications with different run-time requirements on the same physical platform. In scenarios such as autonomous vehicles, these virtualized platforms must handle varying application requirements - from strict temporal predictability to high performance - while simu...
Conference Paper
Full-text available
Studies have shown memory and computational needs vary in-dependently across applications. Recent work has explored using hybrid memory technology (SRAM+NVM) in on-chip memories of multicore processors (CMPs) to support the varied needs of di-verse workloads. Such works suggest architectural modifications that require supplemental management in the...
Conference Paper
Modern heterogeneous CPU-GPU based mobile architectures that execute intensive mobile games and other graphics applications use software governors to achieve high performance with energy-efficiency. For dynamic and diverse gaming workloads on heterogeneous platforms, existing governors typically utilize statistical or heuristic models assuming line...
Article
Full-text available
The Internet of Things (IoT) paradigm holds significant promises for remote health monitoring systems. Due to their life- or mission-critical nature, these systems need to provide a high level of availability and accuracy. On the one hand, centralized cloud-based IoT systems lack reliability, punctuality and availability (e.g., in case of slow or u...
Conference Paper
The memory subsystem is a major contributor to the overall performance and energy consumption of embedded computing platforms. The emergence of "killer" applications such as data-intensive recognition, mining, and synthesis (RMS) applications puts even more stress on the memory subsystem and exacerbates its energy consumption. Traditional mechanism...
Article
Many-core systems are highly complex and require thorough orchestration of different goals across the computing abstraction stack to satisfy embedded system constraints. Contemporary resource management approaches typically focus on a fixed objective, while neglecting the need for replanning (i.e., updating the objective function). This trend is pa...
Article
This letter proposes a system architecture for a scalable software-assisted memory (SAM) hierarchy for emerging manycore embedded systems. Our SAM hierarchy overcomes the coherence overhead and inflexibility of purely hardware-managed memory hierarchies in adapting to variable workloads. Our preliminary results show opportunities for energy saving...
Article
We describe the emerging paradigm of self-aware computing and give an overview of proposed architectures and applications with focus on SoC solutions.
Article
Full-text available
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine intelligent approach for heart-rate estimation from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and usin...
Article
Full-text available
Supported by recent computational studies, sparse coding and dimensionality reduction are emerging as a ubiquitous coding strategy across brain regions and modalities, allowing neurons to achieve nonnegative sparse coding (NSC) by efficiently encoding high-dimensional stimulus spaces using a sparse and parts-based population code. Reducing the dime...
Article
Power capping techniques based on dynamic voltage and frequency scaling (DVFS) and power gating (PG) are oriented toward power actuation, compromising on performance and energy. Inherent error resilience of emerging application domains, such as Internet-of-Things (IoT) and machine learning, provides opportunities for energy and performance gains. L...
Code
CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail. Source code: https://github.com/UCI-CARL/CARLsim3 Documentation: http://www.socsci.uci.edu/~jkrichma/CARLsim/doc
Poster
Full-text available
Poster from Society for Neuroscience (SfN) Annual Meeting 2016. http://www.abstractsonline.com/pp8/#!/4071/presentation/30223
Conference Paper
Full-text available
Power Capping techniques are used to restrict power consumption of computer systems to a thermally safe limit. Current many-core systems employ dynamic voltage and frequency scaling (DVFS), power gating (PG) and scheduling methods as actuators for power capping. These knobs are oriented towards power actuation, while the need for performance and en...
Conference Paper
Many multimedia applications exhibit a phasic behavior. Phasic behavior of applications has been studied primarily focused on code execution. However, temporal variation in an application's memory usage can deviate from its program behavior, providing opportunities to exploit these memory phases to enable more efficient use of on-chip memory resour...
Conference Paper
Full-text available
To meet the performance and energy efficiency demands of emerging complex and variable workloads, heterogeneous many-core architectures are increasingly being deployed, necessitating operating systems support for adaptive task allocation to efficiently exploit this heterogeneity in the face of unpredictable workloads. We present SPARTA, a throughpu...
Conference Paper
The increasing amount of computation in heterogeneous architectures (including CPU and GPU cores) puts a big burden on memory subsystem. With the gap between compute units and the memory performance getting wider, designing a platform with a responsive memory system becomes more challenging. This issue is exacerbated when memory systems have to sat...
Article
Software Programmable Memories, or SPMs, are raw on-chip memories that are not implicitly managed by the processor hardware, but explicitly by software. For example, while caches fetch data from memories automatically and maintain coherence with other caches, SPMs explicitly manage data movement between memories and other SPMs through software inst...
Chapter
In this chapter we consider the issues related to integrating microarchitectural IP blocks into complex SoCs while satisfying performance, power, thermal, and reliability constraints. We first review different abstraction levels for SoC design that promote IP reuse, and which enable fast simulation for early functional validation of the SoC platfor...
Conference Paper
Full-text available
In this paper we propose Run-DMC , an accurate runtime performance and power estimation scheme for dynamic workloads executing on heterogeneous multicore systems. In contrast to previous works, Run-DMC uses fine grain per-thread metrics that model the Thread Load Contribution (TLC) induced by the native OS scheduling policy to accurately predict pe...
Conference Paper
Full-text available
Cyber–physical systems (CPSs) are physical and engineered systems whose operations are monitored, coordinated, controlled, and integrated by a computing, control, and communication core.We propose Cyberphysical-System-on-Chip (CPSoC), a new class of sensor and actuator-rich multiprocessor systemson- chip (MPSoCs), that augment MPSoCs with additiona...
Conference Paper
Full-text available
Cyberphysical systems (CPSs) are physical and en-gineered systems whose operations are monitored, coordinated, controlled, and integrated by a computing, control, and communi-cation core. We propose Cyberphysical-System-on-Chip (CPSoC), a new class of sensor and actuator-rich multiprocessor systems-on-chip (MPSoCs), that augment MPSoCs with additio...
Article
Full-text available
Heterogeneous multicore processors (HMP) present significant advantages over homogenous multiprocessors due to their improved power, performance, and energy efficiency for a given chip/die area. However, due to their diverse and vast design space, selecting a suitable HMP configuration with different core types within a given area-power budget is a...
Conference Paper
Full-text available
Heterogeneous multicore processors (HMP) present significant advantages over homogenous multiprocessors due to their improved power, performance, and energy efficiency for a given chip/die area. However, due to their diverse and vast design space, selecting a suitable HMP configuration with different core types within a given area-power budget is a...
Article
Full-text available
Cyber-Physical Systems-on-Chip (CPSoC) are a new class of sensor- and actuator-rich multiprocessor system-onchips (MPSoCs) whose operations are monitored, coordinated, and controlled using a computing-communication-control (C3) centric core with additional on-chip and cross-layer sensing and actuation capabilities that enable self-awareness within...
Article
1 _______________________________________________________________________ Caches are known to consume a large part of total microprocessor power. Traditionally, voltage scaling has been used to reduce both dynamic and leakage power in caches. However, aggressive voltage reduction causes process-variation-induced failures in cache SRAM arrays, which...
Conference Paper
Full-text available
Graphics processing units are being widely used in embedded systems as they can achieve high performance and energy efficiency. In such systems, the problem of computation and data mapping for multiple applications while minimizing the completion time is quite challenging due to a large size of the policy space, including heterogeneous application...
Conference Paper
Full-text available
This paper presents a scalable and collaborative mobile crowdsensing framework for efficient collective understanding of users, contexts, and their environments. Collaborative mobile crowdsensing enables information to be gathered and shared by users who are directly involved (participatory sensing) or integrated seamlessly as needed (opportunistic...
Conference Paper
Full-text available