Encoding (memory)

About: Encoding (memory) is a research topic. Over the lifetime, 7547 publications have been published within this topic receiving 120214 citations. The topic is also known as: memory encoding & encoding of memories.

Low-power state assignment targeting two- and multilevel logic implementations

Abstract: The problem of minimizing power consumption during the state encoding of a finite-state machine is addressed. A new power cost model for state encoding is proposed, and encoding techniques that minimize this power cost for two- and multilevel logic implementations are described. These techniques are compared with those that minimize area or the switching activity at the present state bits. Experimental results show significant improvements.

High-Density Image Storage Using Approximate Memory Cells

Abstract: This paper proposes tailoring image encoding for an approximate storage substrate. We demonstrate that indiscriminately storing encoded images in approximate memory generates unacceptable and uncontrollable quality degradation. The key finding is that errors in the encoded bit streams have non-uniform impact on the decoded image quality. We develop a methodology to determine the relative importance of encoded bits and store them in an approximate storage substrate. The storage cells are optimized to reduce error rate via biasing and are tuned to meet the desired reliability requirement via selective error correction. In a case study with the progressive transform codec (PTC), a precursor to JPEG XR, the proposed approximate image storage system exhibits a 2.7x increase in density of pixels per silicon volume under bounded error rates, and this achievement is additive to the storage savings of PTC compression.

MASC: Ultra-low energy multiple-access single-charge TCAM for approximate computing

Abstract: Memory-based computing using associative memory has emerged as a promising solution to reduce the energy consumption of important classes of streaming applications such as multimedia by avoiding redundant computations. In associative memory, a set of frequent patterns that represent basic functions are pre-stored in ternary content addressable memory (TCAM) and reused. The primary limitation to using associative memory in modern parallel processors is the large search energy required by TCAMs. In TCAMs, all match rows, except hit rows, precharge and discharge in every search operation, resulting in high and undesirable energy consumption. In this paper, we propose a new multiple-access single-charge (MASC) TCAM architecture which is capable of searching TCAM contents multiple times with a single precharging cycle. In contrast to previous designs, the MASC TCAM keeps the match-line voltage of all miss-rows high and uses their charge for the next search operation, while only the hit rows discharge. We use a periodic refresh scheme to guarantee the accuracy of the search. We also implement a new type of approximate associative memory by setting longer refresh times for MASC TCAMs, which yields search results within 1–2 bit Hamming distances of the exact result. Our evaluation on AMD Southern Island GPU shows that using MASC associative memory can improve the average GPGPU energy efficiency by 36.6%, 40.2% and 39.4% for exact matching, selective 1-HD and 2-HD approximations respectively, with acceptable quality of service (PSNR>30dB). These energy savings are 1.8X and 1.6X higher than GPGPU using exact matching TCAM and approximation TCAM that uses voltage overscaling, respectively.

Locus Coeruleus and Dopamine-Dependent Memory Consolidation

Abstract: Most everyday memories including many episodic-like memories that we may form automatically in the hippocampus (HPC) are forgotten, while some of them are retained for a long time by a memory stabilization process, called initial memory consolidation. Specifically, the retention of everyday memory is enhanced, in humans and animals, when something novel happens shortly before or after the time of encoding. Converging evidence has indicated that dopamine (DA) signaling via D1/D5 receptors in HPC is required for persistence of synaptic plasticity and memory, thereby playing an important role in the novelty-associated memory enhancement. In this review paper, we aim to provide an overview of the key findings related to D1/D5 receptor-dependent persistence of synaptic plasticity and memory in HPC, especially focusing on the emerging evidence for a role of the locus coeruleus (LC) in DA-dependent memory consolidation. We then refer to candidate brain areas and circuits that might be responsible for detection and transmission of the environmental novelty signal and molecular and anatomical evidence for the LC-DA system. We also discuss molecular mechanisms that might mediate the environmental novelty-associated memory enhancement, including plasticity-related proteins that are involved in initial memory consolidation processes in HPC.