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Wally “Walden” Rhines joined Cornami as president and CEO in July 2020, succeeding co-founder Gordon “Gordie” Campbell, who became executive chairman. The hire put an experienced semiconductor and software executive in charge as the roughly 60-person startup prepared to move from technology development toward deployment. Cornami’s bigger bet was not ordinary AI acceleration: it argued its reconfigurable hardware could make fully homomorphic encryption practical for demanding workloads.
This is a retrospective, not a current leadership announcement. Cornami said Rhines stepped down as CEO on June 2, 2025, and Campbell returned to the role. Rhines remained on the board, according to Cornami’s announcement.
What was announced in July 2020?
Cornami named Rhines its president and chief executive officer in July 2020. Campbell, who had co-founded the company and served as CEO, became executive chairman. The company said Rhines would oversee technology development, deployment, and day-to-day operations as it moved toward product and market deployment. The appointment was reported by Design-Reuse and EE Times.
At the time, EE Times reported that Cornami had about 60 employees and had raised just under $30 million. The company said it had an FPGA-based emulation of its chip, expected another three to four months for full verification, and targeted silicon in the first half of 2021. Those were statements and projections made in 2020, not confirmation that the milestones were later achieved.
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Why was Rhines a consequential hire?
Rhines was an industry veteran, not simply an “AI executive.” He led Mentor Graphics for almost 25 years and remained associated with it as CEO Emeritus after Siemens acquired the company in 2017. Before Mentor, he held senior semiconductor responsibilities at Texas Instruments. His background crossed semiconductor products, electronic design automation (EDA) software, corporate strategy, and technology commercialization.
That experience could matter to a young chip company trying to turn an architecture into a product: semiconductor startups must coordinate engineering, financing, manufacturing, software, and customer adoption. The appointment announcement framed Rhines’s role around development and deployment. It does not, by itself, establish that the company successfully commercialized its technology.
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What was Cornami building?
Cornami described its design as a reconfigurable computing fabric: a highly parallel, many-core architecture intended to scale from thousands of cores on a chip to millions across a system. The company said a proprietary high-speed network-on-chip would connect the cores. EE Times characterized the design as a reconfigurable, systolic-array-like fabric, with data flowing through the chip; individual cores could be programmed independently and could use different numerical precisions.
The company presented this architecture as suited to AI and machine-learning workloads such as autonomous driving, robotics, 5G, and data-center computing. Its proposed advantage was parallelism and reduced dependence on conventional patterns of cache and off-chip memory movement. Those descriptions reflect Cornami’s positioning and contemporary reporting; the available material does not independently establish its performance, power, area, programmability, or portability relative to competing processors.
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Why did fully homomorphic encryption change the pitch?
Fully homomorphic encryption (FHE) lets a service perform supported computations directly on encrypted data. In simplified terms, a data owner encrypts information, an outside service processes the ciphertext, and the service returns an encrypted result that only an authorized party can decrypt. The service need not see the underlying data in plaintext during that computation.
That differs from ordinary encryption at rest or in transit, which protects stored or transmitted data but does not enable computation on it. It also differs from a trusted execution environment, where data is decrypted inside protected hardware, and from secure multiparty computation, where parties jointly calculate without disclosing their inputs to one another. Partially or somewhat homomorphic schemes support narrower classes or depths of operations; FHE aims to support much broader computation, with significant costs that depend on the scheme, parameters, circuit, and workload.
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In the 2020 EE Times interview, Rhines said he had examined whether semiconductor technology could accelerate FHE in connection with a DARPA-related effort. He described the prevailing challenge as the enormous performance improvement FHE appeared to require over contemporary CPUs and GPUs. Cornami’s claim that its parallel architecture could help address that bottleneck drew his interest. That was a rationale for the bet, not independent proof that the company had solved FHE’s performance problem.
The potential use cases included cloud analytics, medical-data processing, financial modeling, and AI inference where an organization wants to use sensitive data without exposing it to the infrastructure operator. Cornami’s differentiation was therefore meant to be privacy-preserving computation as much as AI throughput. FHE workloads can be especially demanding in arithmetic and memory; results depend on the encryption scheme, parameter set, circuit depth, precision, and operations such as bootstrapping. A hardware claim is meaningful only when it specifies the workload and compares end-to-end performance with relevant alternatives.
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Why might a startup pursue encrypted computing instead of only AI acceleration?
Rhines’s reasoning, as reported by EE Times, was that general AI acceleration was already crowded, while FHE might offer a more distinct opportunity. Cornami argued that specialized parallel hardware could reduce the latency and cost of encrypted computation. If it worked, that could appeal to cloud providers and financial institutions handling sensitive workloads.
The trade-off is commercial as well as technical. Automotive applications may offer large volumes, but qualification and design cycles can be long. Financial-services and cloud customers may have an immediate interest in confidential computing, yet still demand security assurances, reliable integration, usable software, and credible performance evidence. FHE is a potentially differentiated niche, but it is less mature than conventional AI inference. These market assessments were part of the company’s and Rhines’s rationale, not independently established outcomes.
What did Cornami’s early milestones—and later record—establish?
| Evidence | What it establishes |
|---|---|
| 2020 FPGA-based emulation and projected first-half-2021 silicon, as reported by EE Times | A reported development status and target at the time. It does not verify that production silicon arrived on that schedule. |
| 2022 financing announcement from Cornami and Applied Ventures | Cornami announced a strategic investment from Applied Ventures and a Series C led by SoftBank Vision Fund 2. Financing is evidence of investor backing, not proof of product performance or commercial adoption. |
| 2024 appointment announcement from Cornami | The company appointed cryptographer Craig Gentry as chief scientist for algorithms, consistent with its continued emphasis on FHE. |
| 2025 EE Times coverage of FHE and AI demonstrations: “Cornami targets FHE encrypted AI in real time” | Later reporting described continued demonstrations and product development. Demonstrations do not alone establish broad customer deployment or independently reproduced benchmarks. |
The reviewed material does not establish commercial product availability, volume shipments, named customer deployments, revenue, unit economics, or independent benchmark results. It also does not settle how the original 2021 silicon target compared with actual delivery. A reconfigurable chip’s practical value would depend not just on its cores, but on compilers, libraries, runtime tools, model conversion, and integration with customer systems. The cited sources do not provide enough evidence to answer those product and deployment questions definitively.
What happened to Rhines’s role?
On June 2, 2025, Cornami announced that Rhines had stepped down as CEO and that Campbell, previously executive chairman, had become CEO. Cornami said Rhines would remain on its board. In August 2025, EE Times reported that Rhines had become CEO of EDA company Silvaco while continuing as a Cornami board member. The change means the 2020 appointment should be understood as a historical leadership transition, not a current Cornami CEO listing.
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