Hardware and Architecture

The machinery that powers many of our interactions today — Web search, social networking, email, online video, shopping, game playing — is made of the smallest and the most massive computers. The smallest part is your smartphone, a machine that is over ten times faster than the iconic Cray-1 supercomputer. The capabilities of these remarkable mobile devices are amplified by orders of magnitude through their connection to Web services running on building-sized computing systems that we call Warehouse-scale computers (WSCs).

Google’s engineers and researchers have been pioneering both WSC and mobile hardware technology with the goal of providing Google programmers and our Cloud developers with a unique computing infrastructure in terms of scale, cost-efficiency, energy-efficiency, resiliency and speed. The tight collaboration among software, hardware, mechanical, electrical, environmental, thermal and civil engineers result in some of the most impressive and efficient computers in the world.

Recent Publications

Preview abstract While MVP and CLEAN Architecture are popular Android patterns, they often introduce boilerplate or lack reactivity. This article introduces the Reactive Data Layer Architecture (RDLA), an offline-first, push-based data layer pattern designed for modern Android apps using Jetpack Compose and Room. Using a heart rate tracking example, we demonstrate how RDLA provides robust local-remote synchronization, clean separation of concerns without Use Case overhead, and simplified unit testing via the TestExtensions pattern. View details
Preview abstract Every abstraction layer in the modern software stack exists to solve legitimate problems—coordinating independent developers and enforcing trust across boundaries. However, each layer exacts a Cognitive Tax: overhead paid not for correctness, but for human coordination. Published measurements bound this non-computational overhead at ~59% across the ISA frontend, ABI, IEEE 754 logic, and per-die guard-band slack. We propose a shift from shipping static artifacts to distributing formal intent. Developer intent is translated into Z3 invariant bundles, which a local Neural-Symbolic Oracle then synthesizes into `Asemantic Code'—an artifact governed by load-time proof certificates and mathematically mutated to exploit the specific manufacturing physics of its execution die. View details
Preview abstract Modern compute subsystems have evolved into complex architectures where custom Compute-IPs interface directly or downstream with a mix of in-flight 1st-party IPs (1PIP), stable legacy components, and pre-verified 3rd-party IPs (3PIP). These connections—whether coherent, non-coherent / configuration, for custom use-cases utilizing in-house protocols, etc—often require concurrent development of both the compute tiles and their integration logic to meet aggressive time-to-market goals. However, this parallel approach introduces a critical bottleneck: the subsystem cannot be verified until both the Compute-IP and the 1PIPs reach maturity. Consequently, fundamental functional misalignments—such as protocol handshaking deadlocks, clock and reset sequencing issues, and architectural assumption mismatches—often remain hidden during IP development phases, resulting in a high-risk discovery tail where "integration-killer" bugs are uncovered only when RTL rework costs and schedule impacts are prohibitive. To break this deadlock, we present a verification-driven methodology that utilizes a silicon-proven Golden Proxy, Direct-Execution Traffic Profiles, and Programmable Sequencers to provide a functional proof of concept and pre-pull critical inter-IP interaction mismatch discoveries months prior to traditional integration milestones. View details
Preview abstract SoC Flat IR/EM signoff is generally done for multiple cycles thus generally mandating 2+ days to cover a single scenario- not only is the coverage limited but also expensive since even small ECO fixes trigger full analysis repeat (of same resources). Additionally, designs which have multiple hierarchical block level instantiations - this is massively computationally redundant. Reduced Order Model (ROM) Flow: Hierarchical Abstraction for IR/EM Signoff: ROM eliminates computational redundancy by using abstract representations of pre-verified blocks. It leverages tweaked SoC flat analysis to have appropriate block level details to enable 10-20× faster SoC turnaround and broader scenario coverage. Below is its mechanism: The Common Connection Layer (CCL) acts as the electrical boundary between block & SoC top. ROM preserves full detail only at the CCL and CCL-1, while the lower metal layers (M0 to CCL-2) are rolled up into equivalent impedance model to maintain signoff accuracy. Designers use a mix of detailed instances for same critical block with reduced instances to optimize resource usage as shown in Fig 1. The Validation Problem with ROM- Trust Gap: Context Mismatch: ROMs are generated in standalone conditions, failing to account for top-level grid impedance and adjacent block coupling. Fidelity & Coverage Loss: Abstracting 12-14 layers can mask local voltage violations; current manual spot-checks are insufficient since these fail to quantify if CCL node voltages in all ROM instances match their power-domain & scenario specific simulation values Objective of this work: Systematic validation across all ROM instances & all power domains in a quick (wall time ~mins for SoC) else it would offset ROM runtime benefits. Quantitative fidelity metrics with low violation thresholds & spatial coverage for debug to understand root cause of localised errors. View details
Preview abstract To meet aggressive time-to-market goals, modern mobile SoC architectures require the concurrent development of custom Compute-IPs and surrounding subsystem integration logic (1PIPs and 3PIPs). However, this parallel execution creates a critical verification deadlock: the subsystem cannot be validated until both the Compute-IP and volatile, in-flight 1PIPs reach physical RTL maturity. Consequently, "integration-killer" bugs—such as protocol handshaking deadlocks and clock/reset sequencing mismatches—remain hidden until late in the design cycle when RTL rework costs are prohibitive. To break this bottleneck, we present a verification-driven methodology utilizing a silicon-proven Golden Proxy, Direct-Execution Traffic Profiles, Programmable Sequencers and Automated Protocol Converters. This framework completely decouples parallel hardware dependencies, pre-pulling critical inter-IP mismatch discoveries months ahead of traditional integration milestones. View details
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