Services: Price List

WebFeet Research is a premier market research firm that focuses on in-depth analyses of trends within the semiconductor market.

That memory technology is changing is no surprise to those involved – that it is now beginning to revolutionize computing is a growing expectation of the market. NAND-Flash is nearing a theoretical limit in both lateral shrinks and in the number of layers being good enough for storage but too slow for main memory. Dynamic-RAM is also reaching economical limitations and is likewise under inspection for the technology that will replace it. Enter persistent memory that combines high speed, Byte-addressable DRAM with better non-volatility than Flash. In addition, the processing market is undergoing a sea change where the data will divide into multiple execution units in a data flow type architecture. Some of the data will reside in persistent associative memory execution units tightly coupled to the data flow architecture. How these demands will distribute across the process and memory technology spectrum is the analysis that WebFeet Research delivers.

Service Portfolio 2018

1. In-Memory Database Computing Research Service (RS601-2024)

This service comprises studies that analyze the evolution of solutions using In-Memory Compute architecture executing Analytic functions. Market pressures have increased the need to not only expedite the execution of this function but to extend it to Predictive Analytics as well. This requires the use of Artificial Intelligence technology beyond the Deep Learning perspective. Von Neumann Symbol Computing is adapting to a new generation of Non-von Neumann (NvN) machine capabilities with distributed embedded algorithmic neural networks closely coupled to main memory to achieve a number of other artificial intelligent functions as required (i.e. user programmable). The in-memory NvN Processing Unit can perform additional tasks such as; data, storage, arithmetic, logic, and other computing functions without the need to move data outside the local fabric. Further, this service addresses the In-Memory architecture impacts on Flash memory, Persistent Memory and DRAM.

Artificial Narrow Intelligence – Impact of Deep Learning and its NN Derivatives (RS600DL-2024) Our understanding of Artificial Intelligence has now progressed far enough to better understand its strengths and weaknesses. The base technology stems from the original use of Convolutional Neural Networks (CNN), an entry point into what looked to have a promising future for general use in machine intelligence. This future has fallen short of being able to fulfill that obligation and has been renamed Machine Learning instead. Nevertheless Artificial Narrow Intelligence (ML) is seen as a misnamed leftover on the way to Artificial General Intelligence – it has no real base to link “Intelligence” to but is useful where high levels of classification accuracy are required within a fairly “narrow” subject category. Most of ML is found in Neuromorphic solutions stems from CNN of one sort or another. Generally these solutions require high amounts of training data and supervision to reach a reliable context of use within a system. The implication from the findings of this report is that a more flexible memory framework solution set has evolved and is subtly taking share away from this former industry “workhorse”. That this methodology set has entered into some production levels is problematic for those companies that have entered the market with this technology option with the idea of it becoming a major technology to buttress their IoT entries. The report discusses this with a view to the future and how these current trends will segue into a longer lived and more flexible solution arrangement. One item that is fast moving forward is the use of Persistent NVDRAM within this embedded control, IoTs and Edge computing segment. Additionally, it also points out the need for eNVDRAM for these segments.

Artificial General Intelligence – The Third Wave (RS625AGI-2024) This portfolio builds off ML/DL with the next phase of Artificial Associative Intelligence that is changing the computing processing architecture and is directed toward the future transition to Artificial General Intelligence (AGI). It has become strikingly evident that memory is one of the most prominent elements of human cognition and one that has become increasingly important for artificial intelligence (AI) systems. As AI agents evolve into the third wave and tackle more complex scenarios, the role of memory is not only relevant but has become mandatory. Currently, memory models are one of the most notably missing components of AI platforms and frameworks. This report examines how memory is used in today’s systems and forecasts how it will be transformed into a key element in future Machine Learning and Machine Intelligent systems. Emphasis is placed on hetero-associative memory that can provide one pass training on massive data sets, encode the data into hypervectors, and run hypervector searches efficiently all the while reducing power, vastly increasing performance and maintaining equal or lower cost.

Subjects include DRAM/Flash/XPoint/ReRAM/MRAM/NRAM/FeRAM/HTM/AAM/BAM plus hybrid models and implementations; emergence of, and application of Near Data Computing, and the impact on the von Neumann architecture.

2. Storage Systems Service (SS701-2024)

The main focus of this service analyzes the application devices that contain a significant amount of nonvolatile memory or drive / accelerate the development of nonvolatile memory market for use in a storage application. Target applications are in all three of the major device market segments: consumer, mobile and computing. This service identifies the market requirements and assesses the entire complement of storage technologies and systems that compete for the storage market: Flash Storage (SSD, EFD, Flash Cards), NVDIMM-N/ P/X, Memory Channel Storage and alternative storage technologies.

Solid State Drives (SSD) Markets and Applications - Annual (SS300SSD-2024) The SSD study analyses the technology, markets and applications for SSDs in comparison with hard disk drives. It forecasts the evolution of the computing, consumer, and enterprise markets for SSDs, as well as the technical and commercial challenges SSDs are facing: cost, capacity, reliability, density, temperature range and mechanical ruggedness. Controllers both internal and external for the various types of SSDs are analyzed and forecast by enterprise and computing interface. Flash cache and other NVM caches are also compared and forecast for the enterprise and computing market applications. The annual report includes the SSD forecast out to 2027 and provides breakouts for PCIe, NVMe (PCIe, U.2, M.2), SATA, and NVDIMM-N/P/X.

3. Memory Components Service (CS801-2024)

This service consists of studies that analyze the market and applications for floating gate and trapped charge Flash memory components, XPoint components and embedded Flash devices. Historic data are provided for the last two years, while forecast data for five years to come.

Flash Memory Applications and Markets (CS100FA-2024) The study analyses the demand for Flash memory components (NAND, NOR, Serial NOR, NVRAM). It investigates the current and future system and technology requirements for more than 195 end-use applications like Smart Phones, IoT (Internet of Things) and SSDs, which drive the market for Flash memory components. This demand forecast segments the usage in each application by memory (NOR-type) or storage (NAND-type) and provides capacity breakouts by revenue, units, Mbits/Gbits, and ASPs that are consolidated into the overall demand forecast. Quarterly spreadsheet updates are available for select applications.

Flash Memory Component Forecast – quarterly (CS200CF-2024) The study analyses quarterly the production of floating gate and 3D Flash memory components plus XPoint memory. The Flash components are segmented by capacity for NOR, MLC NOR, serial NOR, Combo (NOR + xRAM), and into NAND, MLC NAND, TLC NAND, Combo (NAND + xRAM), 3D MLC NAND, 3D TLC NAND and XPoint/NVRAM. Forecasts are provided annually five years for revenue, units, and ASPs. Historical results are compiled from the Flash Memory Reporting Association (FMRA) that collects the quarterly shipments from the top Flash manufacturers. Vendor market shares are projected quarterly for the current year.

Non Volatile Memory Vendors – Market Shares (CS700MS-2024) The report summarizes the market data, as well as the ranking and market shares of NOR, serial NOR and NAND Flash memory manufacturers and vendors. It also includes the rankings and market shares for the other three nonvolatile memory markets: (EPROM + MROM: OTP ROM), EEPROM (serial and parallel), and NVRAM. In addition, serial EEPROM is forecast out to 2027 by interface, density, revenue, units, and ASPs, and another forecast is made for NVSRAM by density. Both forecasts are available for additional costs.

Serial EEPROM Forecast (CS770SE-2024) This report provides a forecast for Serial EEPROM by density, interface, and applications. The larger densities >512Kbit are analyzed for conversion to RRAM and other Persistent Memories. The serial E2 applications are forecast for over 50 diverse applications including DRAM modules, e-cigarettes and IoT sensors out through 2024. The impact of COVID-19 has been factored into the 2022-2023 markets and beyond.

Code Storage SWOT / Companies - (CS575NSW-2024) The report provides a SWOT (Strength, Weakness, Opportunities, Threats) analysis on the Code Storage: Serial NOR, Parallel NOR, SLC and SPI NAND market for the top six vendors. Code Storage is forecast out to 2024 by density (256Mbit-8Gbit) for revenue, units, and ASPs for 20 applications. In addition, the serial NOR forecast is segmented by revenue, units, and Mbits for 50+ applications and includes the rankings and market shares for serial NOR. Serial NOR vendor market shares are projected for the automotive, IoT and total market out to 2027.

emNVM Memory – Applications, Markets and Companies (CS400FA-2024) The study analyses the applications and markets for emFlash/emNVM into microcontrollers (8-bit, 16-bit, 32-bit, DSP) and programmable logic (gate arrays, standard cells, field programmable logic). Over forty+ end-use markets many from in the Internet of Things (IoT) are analyzed/quantified by revenue, units, and ASPs for the emFlash/emNVM memory. As Floating Gate NOR ends its lithography scaling, alternative NVM technologies: RRAM, CBRAM, MRAM, NRAM, FeFET, PCM, and NVRAM are poised to fulfill the embedded memory function. Some of these NV Memories will become Persistent Hyperdimensional Associative Memories used in Neuromorphic Computing. The report also profiles companies participating in this emMarket.

The company offers a full complement of technology consulting, management consulting and market research for nonvolatile memory and solid state storage technologies and products. These research services can be tailored for in-depth strategic planning. Through careful analysis of our client’s company goals, financial condition, and competitive position, we assist them in developing, implementing, and monitoring strategies that assist with transitioning to memory centric computing as well as aligning economic, market directions and forecasts. For more information, visit www.webfeetresearch.com.

Price Schedule for Portfolio - 2024

1. In-Memory / Cognitive Intelligence Computing Research Service

RS600DL-2024 Artificial Narrow Intelligence – Impact on Deep Learning and its NN Derivatives $ 7,500

RS625AGI-2024 Artificial General Intelligence – The Third Wave $ 7,500

RS601-2024 Research Service - the above standard reports plus bi-monthly / conference updates with one on-site meeting per year, strategic planning and positioning of cognitive computing / neuromorphic compute, industry trends, company profiles, thought leadership for a six month term $25,000

2. Storage Systems Service

SS300SSD-2024 Solid State Drives (SSD) Markets/Applications (annual) $ 5,995

3. Memory Components Service

CS100FA-2024 Flash Memory Applications & Markets – (annual) $ 6,000

CS200CF-2024 Flash Memory Component Forecast - (quarterly) $ 3,500

CS500NSW-2024 Code Storage SWOT analysis/ companies - (annual) $ 3,995

CS700MS-2024 Flash Memory and NVM Vendors - Market Shares $ 2,500

CS775SE-2024 Serial EEPROM Markets and Applications Forecast $ 2,995

NVSRAM forecast – bought only with CS700MS $ 500

EFS400FA-2024 emNVM Memory – Applications, Markets and Companies $ 5,500

CS801-2024 Memory Components Service - the above standard reports $21,500

Pricing Policy

The site license covers a company business unit in one physical location. Multiple business units or multiple physical locations require a corporate license. Corporate licenses are available for a 50% higher price.

Publication Schedule for Studies – 2024

In-Memory / Cognitive Intelligence Computing Research

RS600RTA Artificial Narrow Intelligence – Impact on Semiconductor Markets 3

RS625AI Artificial General Intelligence – The Third Wave 12

Storage Devices

SS300SSD Solid State Drives (SSD) Markets/Applications 1

SS350SWT Solid State Drives (SSD) SWOT/Companies 8

SS375ESSD Commercial/Industrial Solid State Storage (SSS) Forecast 5

SS450EFD Embedded Flash Drives 11

Memory Components

CS100FA Flash Memory Applications and Markets 3

CS200CF Flash Memory Component Forecast quarterly (3, 6, 9, 12)

CS700MS Flash Memory and NVM Vendors - Market Shares 3

CS400FA emFlash Memory – Applications, Markets and Companies 11