AWEQ: Post-Training Quantization with Activation-Weight Equalization for Large Language Models

Large language models(LLMs) exhibit excellent performance across a variety of tasks, but they come with significant computational and storage costs. Quantizing these models is an effective way to alleviate this issue. However, existing methods struggle to strike a balance between model accuracy and hardware efficiency. This is where we introduce AWEQ, a post-training method that requires no additional training overhead. AWEQ excels in both ultra-low-bit quantization and 8-bit weight and activation (W8A8) quantization. There is an observation that weight quantization is less challenging than activation quantization. AWEQ transfers the difficulty of activation quantization to weights using channel equalization, achieving a balance between the quantization difficulties of both, and thereby maximizing performance. We have further refined the equalization method to mitigate quantization bias error, ensuring the robustness of the model. Extensive experiments on popular models such as LLaMA and OPT demonstrate that AWEQ outperforms all existing post-training quantization methods for large models

Towards on-chip time-resolved thermal mapping with micro-/nanosensor arrays

In recent years, thin-film thermocouple (TFTC) array emerged as a versatile candidate in micro-/nanoscale local temperature sensing for its high resolution, passive working mode, and easy fabrication. However, some key issues need to be taken into consideration before real instrumentation and industrial applications of TFTC array. In this work, we will demonstrate that TFTC array can be highly scalable from micrometers to nanometers and that there are potential applications of TFTC array in integrated circuits, including time-resolvable two-dimensional thermal mapping and tracing the heat source of a device. Some potential problems and relevant solutions from a view of industrial applications will be discussed in terms of material selection, multiplexer reading, pattern designing, and cold-junction compensation. We show that the TFTC array is a powerful tool for research fields such as chip thermal management, lab-on-a-chip, and other novel electrical, optical, or thermal devices

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home

Non-Hermitian topological whispering gallery

In 1878, Lord Rayleigh observed the highly celebrated phenomenon of sound waves that creep around the curved gallery of St Paul's Cathedral in London1,2. These whispering-gallery waves scatter efficiently with little diffraction around an enclosure and have since found applications in ultrasonic fatigue and crack testing, and in the optical sensing of nanoparticles or molecules using silica microscale toroids. Recently, intense research efforts have focused on exploring non-Hermitian systems with cleverly matched gain and loss, facilitating unidirectional invisibility and exotic characteristics of exceptional points3,4. Likewise, the surge in physics using topological insulators comprising non-trivial symmetry-protected phases has laid the groundwork in reshaping highly unconventional avenues for robust and reflection-free guiding and steering of both sound and light5,6. Here we construct a topological gallery insulator using sonic crystals made of thermoplastic rods that are decorated with carbon nanotube films, which act as a sonic gain medium by virtue of electro-thermoacoustic coupling. By engineering specific non-Hermiticity textures to the activated rods, we are able to break the chiral symmetry of the whispering-gallery modes, which enables the out-coupling of topological "audio lasing" modes with the desired handedness. We foresee that these findings will stimulate progress in non-destructive testing and acoustic sensing.This work was supported by the National Basic Research Program of China (2017YFA0303702), NSFC (12074183, 11922407, 11904035, 11834008, 11874215 and 12104226) and the Fundamental Research Funds for the Central Universities (020414380181). Z.Z. acknowledges the support from the China National Postdoctoral Program for Innovative Talents (BX20200165) and the China Postdoctoral Science Foundation (2020M681541). L.Z. acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement 801538. J.C. acknowledges support from the European Research Council (ERC) through the Starting Grant 714577 PHONOMETA and from the MINECO through a Ramón y Cajal grant (grant number RYC-2015-17156)

Identification of Balanced Chromosomal Rearrangements Previously Unknown Among Participants in the 1000 Genomes Project: Implications for Interpretation of Structural Variation in Genomes and the Future of Clinical Cytogenetics

Purpose Recent studies demonstrate that whole-genome sequencing (WGS) enables detection of cryptic rearrangements in apparently balanced chromosomal rearrangements (also known as balanced chromosomal abnormalities, BCAs) previously identified by conventional cytogenetic methods. We aimed to assess our analytical tool for detecting BCAs in The 1000 Genomes Project without knowing affected bands. Methods: The 1000 Genomes Project provides an unprecedented integrated map of structural variants in phenotypically normal subjects, but there is no information on potential inclusion of subjects with apparently BCAs akin to those traditionally detected in diagnostic cytogenetics laboratories. We applied our analytical tool to 1,166 genomes from the 1000 Genomes Project with sufficient physical coverage (8.25-fold). Results: Our approach detected four reciprocal balanced translocations and four inversions ranging in size from 57.9 kb to 13.3 Mb, all of which were confirmed by cytogenetic methods and PCR studies. One of DNAs has a subtle translocation that is not readily identified by chromosome analysis due to similar banding patterns and size of exchanged segments, and another results in disruption of all transcripts of an OMIM gene. Conclusions: Our study demonstrates the extension of utilizing low-coverage WGS for unbiased detection of BCAs including translocations and inversions previously unknown in the 1000 Genomes Project

Cooperative Decision Algorithm for Time Critical Assignment without Explicit Communication

Part 6: Decision AlgorithmsInternational audienceDecentralized time critical assignment is popular in the domains of military and emergency response. Considering the large communication delay, unpredictable environment and constraints, to make a rational decision in time critical context toward their common goal, agents have to jointly allocate multiple tasks based on their current status. This process can be built as a Markov Decision Model when they can share their status freely. However, it is computationally infeasible when explicit communication becomes a severe bottleneck. In this paper, by modelling the decision process as a Partially Observable Markov Decision Process for each agent and building heuristic approaches to estimate the state and reduce the action space, we apply greedy policies in our heuristic algorithms to quickly respond to time critical requirement