Enabling Fine-Grain Restricted Coset Coding Through Word-Level Compression for PCM

Phase change memory (PCM) has recently emerged as a promising technology to meet the fast growing demand for large capacity memory in computer systems, replacing DRAM that is impeded by physical limitations. Multi-level cell (MLC) PCM offers high density with low per-byte fabrication cost. However, despite many advantages, such as scalability and low leakage, the energy for programming intermediate states is considerably larger than programing single-level cell PCM. In this paper, we study encoding techniques to reduce write energy for MLC PCM when the encoding granularity is lowered below the typical cache line size. We observe that encoding data blocks at small granularity to reduce write energy actually increases the write energy because of the auxiliary encoding bits. We mitigate this adverse effect by 1) designing suitable codeword mappings that use fewer auxiliary bits and 2) proposing a new Word-Level Compression (WLC) which compresses more than 91% of the memory lines and provides enough room to store the auxiliary data using a novel restricted coset encoding applied at small data block granularities. Experimental results show that the proposed encoding at 16-bit data granularity reduces the write energy by 39%, on average, versus the leading encoding approach for write energy reduction. Furthermore, it improves endurance by 20% and is more reliable than the leading approach. Hardware synthesis evaluation shows that the proposed encoding can be implemented on-chip with only a nominal area overhead.Comment: 12 page

Energy Saving Techniques for Phase Change Memory (PCM)

In recent years, the energy consumption of computing systems has increased and a large fraction of this energy is consumed in main memory. Towards this, researchers have proposed use of non-volatile memory, such as phase change memory (PCM), which has low read latency and power; and nearly zero leakage power. However, the write latency and power of PCM are very high and this, along with limited write endurance of PCM present significant challenges in enabling wide-spread adoption of PCM. To address this, several architecture-level techniques have been proposed. In this report, we review several techniques to manage power consumption of PCM. We also classify these techniques based on their characteristics to provide insights into them. The aim of this work is encourage researchers to propose even better techniques for improving energy efficiency of PCM based main memory.Comment: Survey, phase change RAM (PCRAM

How to Knit Your Own Markov Blanket

Hohwy (Hohwy 2016, Hohwy 2017) argues there is a tension between the free energy principle and leading depictions of mind as embodied, enactive, and extended (so-called ‘EEE1 cognition’). The tension is traced to the importance, in free energy formulations, of a conception of mind and agency that depends upon the presence of a ‘Markov blanket’ demarcating the agent from the surrounding world. In what follows I show that the Markov blanket considerations do not, in fact, lead to the kinds of tension that Hohwy depicts. On the contrary, they actively favour the EEE story. This is because the Markov property, as exemplified in biological agents, picks out neither a unique nor a stationary boundary. It is this multiplicity and mutability– rather than the absence of agent-environment boundaries as such - that EEE cognition celebrates

Entropy and perpetual computers

A definition of entropy via the Kolmogorov algorithmic complexity is discussed. As examples, we show how the meanfield theory for the Ising model, and the entropy of a perfect gas can be recovered. The connection with computations are pointed out, by paraphrasing the laws of thermodynamics for computers. Also discussed is an approach that may be adopted to develop statistical mechanics using the algorithmic point of view.Comment: Based on Chanchal Majumdar memorial lectures given in Kolkata. 9 pages, 3 eps figures. For publication in "Physics Teacher"; v2. Sec 3 fragmented into smaller subsection

Study of information transfer optimization for communication satellites

The results are presented of a study of source coding, modulation/channel coding, and systems techniques for application to teleconferencing over high data rate digital communication satellite links. Simultaneous transmission of video, voice, data, and/or graphics is possible in various teleconferencing modes and one-way, two-way, and broadcast modes are considered. A satellite channel model including filters, limiter, a TWT, detectors, and an optimized equalizer is treated in detail. A complete analysis is presented for one set of system assumptions which exclude nonlinear gain and phase distortion in the TWT. Modulation, demodulation, and channel coding are considered, based on an additive white Gaussian noise channel model which is an idealization of an equalized channel. Source coding with emphasis on video data compression is reviewed, and the experimental facility utilized to test promising techniques is fully described

Sparse Signal Processing Concepts for Efficient 5G System Design

As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces