Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

Objective. Bioelectronic medicine is an emerging field that aims at developing closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat a wide range of disorders. When designing a closed-loop protocol for real time modulation o ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. Results show that traditional OLTP systems mostly under-utilize the available micro-archi ...

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

Fast and accurate transmission line outage detection can help the central control unit to respond rapidly to better maintain the security and reliability of power systems. It is especially critical in the situation of multiple line outages which is more li ...

With FPGAs facing broader application domains, the conversion of imperative languages into dataflow circuits has been recently revamped as a way to overcome the conservatism of statically scheduled high-level synthesis. Apart from the ability to extract pa ...

Database systems access memory either sequentially or randomly. Contrary to sequential access and despite the extensive efforts of computer architects, compiler writers, and system builders, random access to data larger than the processor cache has been s ...

In order to improve their power efficiency and computational capacity, modern servers are adopting hardware accelerators, especially GPUs. Modern analytical DMBS engines have been highly optimized for multi-core multi-CPU query execution, but lack the nece ...

We investigate the benefits of known partial support for the recovery of joint-sparse signals and demonstrate that it is advantageous in terms of recovery performance for both rank-blind and rank-aware algorithms. We suggest extensions of several joint-spa ...

In order to optimize the energy use of servers in Data Centers, techniques such as power capping or power budgeting are usually deployed. These techniques rely on the prediction of the power and execution time of applications. These data are obtained via d ...

Index joins present a case of pointer-chasing code that causes data cache misses. In principle, we can hide these cache misses by overlapping them with computation: The lookups involved in an index join are parallel tasks whose execution can be interleaved ...

Modern cloud data centers (DCs) need to tackle efficiently the increasing demand for computing resources and address the energy efficiency challenge. Therefore, it is essential to develop resource provisioning policies that are aware of virtual machine (VM ...

To reduce the average memory access time, most current processors make use of a multilevel cache subsystem. However, despite the proven benefits of such cache structures in the resulting throughput, conventional operations such as copy, simple maps and red ...

In recent years, compressed sensing techniques have been applied to the reconstruction of parallel magnetic resonance (MR) images. Particularly for 3D MR signal, it is crucial to acquire fewer samples to reduce the distortions caused by long-time acquisiti ...

Caching the results of intermediate query results for future re-use is a common technique for improving the performance of analytics over raw data sources. An important design choice in this regard is whether to lazily cache only the offsets of satisfying ...

Software network functions promise to simplify the deployment of network services and reduce network operation cost. However, they face the challenge of unpredictable performance. Given this performance variability, it is imperative that during deployment, ...

The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, adva ...

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

This paper presents DynOR, a 32-bit 6-stage OpenRISC microprocessor with dynamic clock adjustment. To alleviate the issue of unused dynamic timing margins, the clock period of the processor is adjusted on a cycle-by-cycle level, based on the instruction ty ...

Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes

Chattez avec Graph Search

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

Micro-architectural analysis of in-memory OLTP: Revisited

Micro-architectural Analysis of Database Workloads

Multiple Line Outage Detection in Power Systems by Sparse Recovery Using Transient Data

Speculative Dataflow Circuits

Improving Main-memory Database System Performance through Cooperative Multitasking

Hardware-conscious Query Processing in GPU-accelerated Analytical Engines

Joint Sparsity with Partially Known Support and Application to Ultrasound Imaging

Fast Energy Estimation Through Partial Execution of HPC Applications

Interleaving with coroutines: a systematic and practical approach to hide memory latency in index joins

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

Exploiting Compute Caches for Memory Bound Vector Operations

3D Bpconvnet To Reconstruct Parallel Mri

Adaptive Cache Mode Selection for Queries over Raw Data

Automated Synthesis of Adversarial Workloads for Network Functions

The Mondrian Data Engine

An Adaptive Sublinear-Time Block Sparse Fourier Transform

DynOR: A 32-bit Microprocessor in 28 nm FD-SOI with Cycle-By-Cycle Dynamic Clock Adjustment