Hot chips - is it a real ´challenge´?

Special Issue on Hot Chips 2024

The scope of the project is to develop Potato slicer attached with multi-blade as compared to the regular Potato slicer to provide to use both alternatively in domestic & Professional Fields, intended to attract hot potato chips makers. Details of the product development and its features are enclosed. Professionals & Home makers are the large market for Household Manufacturers. Many Manufacturers have developed various strategies to attract the Home makers & Professionals. As student of M-Tech (Product design and Manufacturing), we have made an attempt to address this target group by developing different strategy of providing multi-blade potato slicer which helpful for Home makers & Professionals. In general, this project covers almost all the phases of product design and development.

In Domestic field & Professional life situations like that where a home maker or Professional may need to use potato slicer to make potato chips. Usually, regular potato slicer is used by small and medium range hot potato chips maker, but it consumes both time and energy of the chips maker because of its single blade. By introducing multi-blade in potato slicer, we can save the energy and time of the chips maker. Potato slicer with multi blade will not only save the energy and time of the chips maker, it also increase the production rate of the potato chips. For example slicer with three blades will increase the 3 times production of the regular slicer.

This special issue of IEEE Micro is devoted to selected top-pick articles presented at Hot Chips 2023. The Hot Chips Conference serves as a leading venue for presenting the technical details of innovative microchips on a wide range of topics, including computing, memory, interconnection, and cooling technologies. This particular issue features articles from AMD, Intel, UC Berkeley, Samsung, Cerebras, and Fabric8Labs on different topics including server CPUs, photonic interconnects, processing-in-memory, and artificial intelligence accelerators, as well as new cooling technologies.

The Hot Chips conference has served as a leading venue for presenting architectural details of new chips and chip-related technologies, from established industry leaders, startups, and academia. This article presents an introduction to the seven articles that are chosen to be in the IEEE Micro HotChips Special Issue of 2023.

This article presents an overview of the special issue that contains papers from the 2022 Hot Chips Symposium. The IEEE Micro Editor-in-Chief also congratulates the 2022 Turing Award winner Dr. Robert Metcalfe and reprints a few quotes from his 1976 paper on Ethernet.

Performance analysis of drills with structured surfaces when drilling CFRP/AA7075 stack under MQL condition

The thermal deformation problem is quite serious for the workbench of the environmental dry hobbing machine due to the thermal accumulation of hot chips. A better understanding of the quantity and optimization of the chip repose angle is quite necessary to reduce the workbench thermal deformation. Hence, this paper focuses on the chip repose angle modeling and optimization for the workbench of the dry hobbing machine. Firstly, the dynamic flow characteristics of chips are clarified by analyzing the chip generation mechanism and the motion trajectory of dry hobbing. Then, the chip repose angle is mathematically characterized with consideration of the chip rolling characteristics, with which a chip repose angle optimization model is established by minimizing the thermal accumulation on the workbench, and a chip repose angle optimization method is proposed based on the intelligent optimization algorithm. Finally, the effectiveness of the proposed method is analyzed through the simulation experiment on the dry hobbing of automotive reverse gear. The results show that the maximum overall thermal deformation is reduced by 8 μm for the workbench, and the skewness is reduced by 32% for the workbench spindle with the help of the proposed optimization method. The study provides an effective solution for the quantitative analysis and optimal design of chip repose angle on the workbench of the dry hobbing machine.

The articles in this special section are focus on new chip technologies presented at the Hot Chips 33 Conference held in August 2021. The Hot Chips Conference has served as a leading venue for presenting the technical details of innovative chips designed by academics, startup companies, and established leaders in the field. The conference in 2021 included presentations on a wide range of chips and upcoming chip and packaging technologies. The program committee carefully selected several presentations for which we invited the authors to write an article. Following the customary review process, four articles were accepted to be included in this special issue. These articles describe central processing units (CPUs) that are used in a broad range of products from servers and desktops to mobile solutions, a chip for accelerating AI recommendations, and an HBM2 chip that includes in-memory processing capability. As process technologies continue to provide more transistors per die, each of these chips shows the continuing trend of using those transistors to deliver more functionality per part.

This issue features selected articles from the Hot Chips 33 Symposium, held virtually in August 2021. COVID-19 forced Hot Chips to be a virtual event again; however, the chips presented at the event were really interesting and more powerful than ever! Whether it is artificial intelligence (AI) acceleration or sheer increase in traditional compute capability, emerging chip designs are significant enhancements over their predecessors. New chips are announced every month, and AI accelerators are influencing applications from the cloud to the edge.

Machine learning (ML) recommendation workloads have demanding performance and memory requirements and, to date, have largely been run on servers with x86 processors. To accelerate these workloads (and others), Esperanto Technologies has implemented over 1,000 low-power RISC-V processors on a single chip along with a distributed on-die memory system. The ET-SoC-1 chip is designed to compute at peak rates between 100 and 200 TOPS and to be able to run ML recommendation workloads while consuming less than 20 W of power. Preliminary data presented at the Hot Chips 33 Conference projected over a hundred times better performance per watt for an Esperanto-based accelerator card versus a standard server platform for the MLPerf Deep Learning Recommendation Model benchmark.

Abstract Accuracy requirements for machine tools demand an accurate positioning of the tool center point. Due to the heat sources, for example the friction and heat loss of motors, a machine can undergo complicated deformations during operation. While the location of mounted sources are known in advance, there are also process dependent sources, like hot chips after chip off. Furthermore many material parameters and most coupling parameters are not known exactly, or have an unknown temperature dependency. We consider a coupled thermo‐elastic finite element model of a simplified machine tool. We include uncertain heat sources and exchange parameters and present an optimal sensor placement approach to capture the sources.

Our aim was to determine whether alcohol hangover is associated with eating unhealthy foods (hot chips, soft drink) or healthy foods (fruit, vegetables). Daily diary study across 13 days (micro-longitudinal design). We examined a sample of 605 young adults (71% women; ages 17-25; mean age 19.91 [SD 1.86] years) who completed daily diaries in the university community and reported drinking alcohol at least twice during the 13-day study period. Each day, participants reported on their hangover severity, their consumption of fruit, vegetables, hot chips (French fries), and soft drink, and their alcohol consumption from the previous day. Linear mixed models were used to examine within-person associations between hangover severity and food consumption, by gender. Exploratory models also controlled for previous day alcohol consumption to acknowledge potential variability in hangover susceptibility. On days when participants reported higher severity of hangovers, they reported consuming more hot chips (β = .09, p = .001), more soft drink (β = .08, p = .001) and less fruit (β = -.06, p = .05). In our exploratory model controlling for previous day alcohol consumption, the predictive effect of hangover severity on hot chips remained (β = .08, p = .009) and significant interaction effects were observed between gender and previous day alcohol consumption on fruit (β = -.03, p = .003) and vegetable (β = -.03, p = .03) servings. Higher hangover severity may lead to greater intake of some unhealthy foods such as hot chips, an effect that may not be reduceable to those associated with alcohol consumption per se. Interventions that target excessive drinking primarily, but also emphasize the importance of a healthy diet, should be considered for this population.

This article presents a control system for a cutting tool condition supervision, which recognises tool wear automatically during turning. We used an infrared camera for process control, which—unlike common cameras—captures the thermographic state, in addition to the visual state of the process. Despite challenging environmental conditions (e.g., hot chips) we protected the camera and placed it right up to the cutting knife, so that machining could be observed closely. During the experiment constant cutting conditions were set for the dry machining of workpiece (low alloy carbon steel 1.7225 or 42CrMo4). To build a dataset of over 9000 images, we machined on a lathe with tool inserts of different wear levels. Using a convolutional neural network (CNN), we developed a model for tool wear and tool damage prediction. It determines the state of a cutting tool automatically (none, low, medium, high wear level), based on thermographic process data. The accuracy of classification was 99.55%, which affirms the adequacy of the proposed method. Such a system enables immediate action in the case of cutting tool wear or breakage, regardless of the operator’s knowledge and competence.

The articles in this special section were presented at Hot Chips 32 which was held virtually on August 16-18, 2020.

Abstract Accuracy requirements for machine tools demand an accurate positioning of the tool center point. Due to the heat sources, for example the friction and heat loss of motors, a machine can undergo complicated deformations during operation. While the location of mounted sources are known in advance, there are also process dependent sources, like hot chips after chip off. Furthermore many material parameters and most coupling parameters are not known exactly, or have an unknown temperature dependency.We consider a coupled thermo‐elastic finite element model of a simplified machine tool. We include uncertain heat sources and exchange parameters and present an optimal sensor placement approach to capture the sources.

The articles in this special section focus on high performance interconnects. In this issue, you will find the best papers on the hottest, most cutting edge interconnects design occurring in industry and academia from this year’s IEEE Symposium on High Performance Interconnects (Hot Interconnects). Like our sister conference, Hot Chips, Hot Interconnects is a choice venue for revealing the latest and greatest advances in hardware. This year at Hot Interconnects was different than past events as it was virtual due to the COVID-19 pandemic. Hot Interconnects attendance was excellent, welcoming approximately 1000 attendees. This year at Hot Interconnects we were pleased to welcome talks from network leaders from NVIDIA, AWS, Ayar Labs, and GigaIO. NVIDIA’s CTO Michael Kagan laid out a case arguing that “Data center is a computer.” Brian Barrett talked about the challenges of designing network technologies for AWS. Scott Taylor from GigaIO and Mark Wade from Ayar Labs introduced new network technologies.

The design of machine tools strongly depends on the materials chosen. Increasing requirements on machine tools require the joint optimization of material and design and thus also drive the development of new materials in this field. Digital technologies finally creating a digital shadow of the machine in development also enable the required co-development taking into consideration dynamic, thermal and long term influences and behavior, enabling state and health monitoring to increase the performance of the machine tool to the maximum possible. The choice of material for the different components of machine tools is today even more difficult than ever. The recent review paper by Möhring et al. [1] sheds light on the vast field of properties and decision opportunities of combining materials at hand with design features. In former times, cast iron was the predominant material for machine bodies and has left its footprints on the design of machine tool bodies lasting still up to now. Because massive machine bodies have been the wealth of good properties, high accuracy, stiffness, good material damping properties have been attributed to cast iron design, then with increasing strength requirements higher strength cast irons came into fashion having much less material damping and finally lead to welded frames. Today requirements of dynamics and thermal behavior change the scene again. The goal is to achieve high productivity with high accuracy, which typically is a contradiction. But increasing dynamics requires distinguishing between moving bodies and their non-moving counterparts, and opens the floor for multimaterial design. For moving parts, which have to move with high dynamics meaning, high speed, high acceleration, high jerk, light weight design prevailed with the utilization of standard materials. Because manufacturability plays a major role, the bionic structures have to be degraded to thin walled rib structures as demonstrated in Fig. 1, while in future additive manufacturing will remove that restriction and enable some real bionic structures. Furthermore material choice has a huge impact on inertia savings which opens the door for CFRP, which becomes especially interesting, when the anisotropy of this material is exploited as shown in Fig. 2. From the manufacturability truss structures then result shown in Fig. 3. For the nonmoving elements, the base body, cast iron, welded steel, polymer cast, and concrete are typical materials chosen. Also aluminium structures are discussed despite the fact that aluminium has only one third of the stiffness of steel, but it offers much better thermal conductivity equalizing temperature differences faster and thus reduces the warp of the structure, which typically causes larger errors than an isotropic thermal expansion. For the choice of materials no generalizable guideline exists. The question which material is the better choice is not answerable in generality, because design follows material, which means that a sound comparison requires completely new design approaches for the different materials, where the difference between metal and polymer concrete or CFRP is really large, offering different potentials. As an example, a design of a fast moving bridge of a gantry machine might be considered. The guiding of a support on this bridge with roller guidings imposes severe problems to the design due to the material mix and different thermal expansion coefficients. Thus the choice of CFRP for the bridge necessarily must be followed up by a decision of the guiding principle, where in this case aerostatic bearings were considered as the most promising possibility. Also the potentials for function integration into the material are of major interest for the material choice, as this is easily possible for low temperature castings like for mineral cast, CFRP, or concrete. This integration of functionalities actually is a fairly new approach and relates again the machine body design to inspiration from biology, as for instance trees or leaves are from the point of view of materials weaker than our technical materials, but have a fine integration of functionalities as transmittance of information and nourriture. Sensor integration opens the field for “feeling machines” also inspired from biology, which enables the machine to detect its embedding environment and react accordingly. Cheap and miniaturized sensors are on the other side the developments that enable this approach of machine design. In the age of compensation, Industrie 4.0 and biological transformation, this functional integration will have a huge impact on material choice. Also in terms of thermal issues in machine tools, the material choice plays a major role, as thermal elongation is a physical property which is influenced by material choice. A much larger influence comes from design as indicated already above. With growing importance of compensation besides sensor integration, especially the thermal linearity and reproducibility are of crucial importance, which makes multi material design a non-trivial design task. The discussion on the superiority of thermally fast reacting machines or thermally slow reacting machines has not come to an end yet. Problematic are machines composed of components that react fast and those that react slow. A major step in that direction is the discovery of thermal resonances in [5], which shows that temperature change frequencies can depending on the machine design lead to higher or lower thermal displacements of the TCP and therefore need to be taken into account in the design phase and are significantly influenced by the choice of materials. Restrictions and influences are also coming from the process a machine tool has to enable. The material choice must take into account the influence of different media as for instance the metal working fluids as well as the debris like hot chips etc. The aforementioned discussion is mainly a discussion of main structural parts of machine tools. It must be pointed out that a machine tool is more than the sum of its structural elements, as also covers, which typically get forgotten in all academic discussion of behaviors of machine tools, but are significant for the influence of the environment on the machine tool. Also here the material choice plays a major role. Finally material choice to a large extent decides on the costs of a machine tool, but due to the huge amount of influence factors a sound fact based decision requires a nearly full design elaboration of various material choices and the summation of costs at the end of this process. This special issue with its various individual papers elucidates different aspects of the influence of materials on the design of machine tools without being capable of offering clear rules for material choice. ===danraku===1) Isolating material to exclude environmental influences on machine tools is proposed. ===danraku===2) A new guiding system with rollers and sliding guidings is proposed and the different materials for the sliding part are investigated. ===danraku===3) Gears from bamboo fibres are proposed and the manufacturability as well as their performance are discussed. The gears offer great advantages from the environmental point of view. ===danraku===4) CFRP for spindle shafts is evaluated and CFRP spindles are compared with steel spindles within the same geometric boundary conditions. The performance increase in compliance and thermal stability is significant. ===danraku===5) A topological optimization of a grinding machine tool structure is presented and showed drastically increased performance. The difficulty to transfer it to a mass producible machine tool structure is pointed out. ===danraku===6) A design of a CFRP ram for a high speed stamping press is presented and testing procedures to ensure the ability of the ram to withstand billions of impacts are designed and carried out. ===danraku===7) CFRP can beneficially applied for the cutting tool structure and besides enhancing dynamics in terms of mass and damping the material also is a valuable basis for smart tools. There are good arguments for each of the materials, which cover the whole scope of machine tool functionality: manufacturability, stiffness, strength, specific mass, thermal properties, function integrability, reproducibility, availability, environmental friendliness, and costs.

The articles in this special section report on the technologies and events that were part of the 31st Annual Hot Chips symposium was held at Stanford University in August 2019.