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TPU

TPU is an initialism with several meanings. The most common are in science and technology and other fields: In science and technology: Other uses:

Science and technology

Tensor Processing Unit

The (TPU) is an (ASIC) developed by , optimized specifically for performing tensor operations that form the core computations in neural networks for workloads. Designed to accelerate both training and inference phases of models, TPUs emphasize high throughput for matrix multiplications and convolutions while minimizing latency and power consumption compared to general-purpose processors like CPUs or GPUs. This specialization makes them particularly effective for large-scale applications in data centers, where they handle the massive parallel computations required for models involving billions of parameters. Google initiated TPU development in response to the growing demands of neural networks in its services, with the first generation deployed internally in 2015 to power inference tasks in products such as Search, Ads, Photos, and Translate. The technology was publicly announced at Google I/O in May 2016, marking a shift toward custom hardware for AI acceleration. Subsequent generations expanded capabilities to include training, with public availability through Google Cloud starting in 2018. Over the years, TPUs have evolved through multiple iterations, each improving performance, memory bandwidth, and scalability via larger pods of interconnected chips. Key architectural features of TPUs include a architecture, which efficiently performs matrix multiplications by streaming data through a grid of processing elements, reducing data movement overhead and enabling high peak throughput. Early versions featured high-bandwidth memory (HBM) integrated on-chip for fast access to weights and activations, with later models incorporating advanced interconnects like optical circuit switches for pod-scale communication. TPUs are tightly integrated with the framework, allowing seamless compilation of models into TPU-optimized executables via tools like XLA (Accelerated Linear Algebra), which supports both and workflows. The evolution of TPU versions reflects Google's focus on scaling AI capabilities, with representative specifications summarized below:
VersionRelease YearKey Features and Performance
v120158-bit integer operations for inference; 92 TOPS peak performance; 40 TOPS/W efficiency; 24 MB HBM; systolic array with 65,536 ALUs.
v22017Added bfloat16 floating-point support for training; pods up to 512 chips with custom high-speed interconnects; ~180 TFLOPS floating-point in early configurations.
v32018Liquid-cooled for higher density; 123 TFLOPS bf16 per chip; 32 GB HBM at 900 GB/s; pods up to 1,024 chips delivering 126 petaFLOPS.
v42020275 TFLOPS bf16 or int8 per chip; 32 GB HBM at 1,200 GB/s; optical circuit switches; pods up to 4,096 chips for 1.1 exaFLOPS.
v5e2023197 TFLOPS bf16 per chip; 16 GB HBM at 819 GB/s; optimized for cost-efficient inference and fine-tuning; supports up to 256-chip slices.
v5p2023459 TFLOPS bf16 per chip; 95 GB HBM3 at 2,765 GB/s; 3D torus interconnect at 4,800 Gbps; pods up to 8,960 chips for training large models like PaLM.
TPUs are primarily applied in data centers to accelerate and , enabling faster iteration on models for tasks like and , with power efficiency exemplified by v1's 40 /W metric that set early benchmarks for specialized hardware. As of 2025, TPUs are widely deployed via Cloud, powering multimodal models such as and supporting generative at scale through recent advancements like the sixth-generation (2024, >4.7x performance over v5e) and seventh-generation (announced April 2025, 4,614 TFLOPS per chip with 192 GB HBM for exascale pods). Compared to Nvidia GPUs, TPUs offer superior speed for tensor-specific operations in optimized workloads but are less versatile for non-AI tasks. This positions TPUs as a key element in broader hardware trends toward domain-specific accelerators.

Thermoplastic polyurethane

Thermoplastic polyurethane (TPU) is a versatile classified as a linear consisting of alternating hard and soft segments. The soft segments, typically derived from long-chain polyols such as polytetramethylene ether glycol (PTMEG), provide flexibility and elasticity, while the hard segments, formed from diisocyanates like (MDI) and short-chain diols, contribute strength and rigidity through physical cross-linking via hydrogen bonding. The development of TPU traces back to the , when chemists at in explored polyurethane systems for elastomeric applications, building on Otto Bayer's earlier 1937 invention of polyurethane chemistry. Commercial advancements followed in the late , with introducing fibers based on similar polyurethane elastomers and BF Goodrich (later ) launching the first dedicated TPU under the Estane brand in 1959; widespread industrial production began in the 1960s, enabling melt-processable alternatives to vulcanized rubber. TPU exhibits a unique combination of properties that bridge plastics and rubbers, including high elasticity with Shore A hardness typically ranging from 60A to 95A, allowing tailoring from soft gels to rigid materials. It demonstrates excellent abrasion resistance, tensile strength up to 50 , and good chemical resistance to oils and solvents, alongside suitable for skin contact. As a , TPU can be melted and reprocessed at temperatures of 180–220°C without chemical , facilitating efficient manufacturing while maintaining durability under dynamic loads. Synthesis of TPU involves a polyaddition where diisocyanates react with and chain extenders in a one-shot or prepolymer process, often via for complex parts or for films and profiles. The flexibility of the final material is influenced by polyol chain length—longer chains enhance softness and elongation—while controlling the hard-to-soft segment ratio allows customization of mechanical performance. Industrial applications of TPU leverage its processability and resilience, including filaments for to produce flexible prototypes, midsoles in athletic footwear such as (using expanded TPU for energy return), seals and hoses in automotive components, medical tubing for catheters, and protective coatings for wires and surfaces. Global production exceeds 500,000 tons annually as of 2025, driven by demand in consumer and industrial sectors. Environmentally, TPU supports through recyclability via melt reprocessing, reducing in manufacturing cycles, though challenges persist with slow of discarded particles contributing to microplastic in ecosystems. Emerging bio-based variants, incorporating renewable polyols from plant sources, offer improved biodegradability while preserving performance, with research focusing on enzymatic breakdown to mitigate long-term environmental impacts.

Transcranial pulsed ultrasound

Transcranial pulsed (TPU), also known as low-intensity transcranial (LITUS), is a non-invasive technique that employs low-intensity, low-frequency waves to stimulate specific regions through the intact . Typically operating at frequencies between 0.5 and 7 MHz and with spatial-peak pulse-average intensities (I_sppa) below 720 mW/cm², TPU delivers pulsed acoustic to modulate neural activity with millimeter-scale . This technique emerged in the early , building on foundational research in for . Seminal studies, such as the 2010 demonstration of ultrasound-induced action potentials in circuits, paved the way, with human applications advancing from 2014 onward, showcasing focal without tissue damage. The primary mechanism of TPU involves acoustic pressure waves that exert mechanical effects on neuronal membranes and channels, potentially through acoustic streaming, , or direct membrane deformation, thereby modulating neuronal excitability without relying on thermal or ionizing effects. Key parameters include (PRF) ranging from 1 to 10 kHz, which allows for precise temporal control of stimulation. TPU has shown promise in experimental treatments for neurological disorders, including , where it enhances motor function and dexterity in clinical trials; , targeting mood-regulating circuits; and , promoting and . As of 2025, ongoing clinical trials demonstrate its efficacy in altering blood-oxygen-level-dependent (BOLD) signals observable via functional MRI (fMRI), confirming targeted . Regarding safety, TPU operates via non- mechanisms and adheres to FDA diagnostic guidelines, maintaining intensities well below thermal damage thresholds, though necessitates input intensities up to several times higher than in to achieve effective stimulation. It holds investigational status from the FDA for applications. Recent advancements include integration with modalities like MRI for precise targeting and the development of portable TPU s to facilitate broader clinical and research use. Additionally, there is potential synergy with AI-driven imaging analysis to optimize stimulation parameters. ===== END CLEANED SECTION =====

Other uses

Tomsk Polytechnic University

Tomsk Polytechnic University (TPU), a leading technical institution in Russia, traces its origins to 1896 when it was established as the Tomsk Technological Institute of Practical Engineers by Emperor Nicholas II, marking the first engineering higher education facility east of the Urals. Dmitri Mendeleev, the renowned chemist and periodic table creator, contributed to its founding efforts despite initial reservations about establishing a separate technical institute in Siberia. The institution underwent several name changes amid Soviet-era reorganizations, becoming the Tomsk Polytechnic Institute in 1944 to reflect its broadened engineering focus, and achieving full university status in 1991. In 2009, TPU was awarded National Research University status, elevating it to a federal research university with enhanced funding for innovation and global collaboration. The main campus is situated in , , encompassing 32 academic and laboratory buildings, 15 residence halls, and advanced facilities such as a research reactor for materials testing and a cluster supporting computational simulations in and physics. As of 2025, TPU enrolls over 11,500 students, including more than 3,000 international scholars from 39 countries, and employs 1,177 , with 256 holding doctoral degrees. This scale underscores its role as a major hub for technical education in Russia's Asian region, fostering a diverse community through academic exchanges in 18 countries. TPU's academic structure features 10 research and engineering schools organized into 21 divisions, spanning disciplines like , , and energy systems. It offers 28 bachelor's, master's, 5 specialist, and 19 postgraduate programs, alongside 395 courses, with flagship offerings in —ranked 30th globally by QS (2025)—and , emphasizing practical applications in resource extraction and advanced composites. These programs integrate hands-on work and partnerships to prepare graduates for high-demand sectors. Among TPU's key achievements are its more than 100,000 , who include Nobel laureate in chemistry Nikolay Semenov and influential engineers shaping Soviet and Russian industry. The university collaborates closely with state entities like for R&D and engages in international exchanges via programs such as Erasmus+, facilitating student and faculty mobility with over 40 overseas partners. Research productivity is robust, with 1,700 annual publications in and Scopus-indexed journals, including 650 in top-quartile outlets, and over 120 patents granted yearly, contributing to innovations in energy and materials. By recent years, cumulative output bolsters Russia's technological self-sufficiency. In recent years, TPU has prioritized and education through specialized initiatives, such as master's programs in environmentally friendly energy conversion technologies using and renewables, and advanced engineering schools training specialists for the fuel and sector. Enrollment has expanded to over 11,500 students post-2020, driven by new and technology tracks amid Russia's priorities. TPU also plays a vital role in training engineers for tech industries, including hardware development essential for computational advancements. Since 2022, geopolitical tensions and sanctions have strained funding and collaborations for universities, including TPU, leading to reduced foreign grants and exchange opportunities. Nonetheless, the institution has demonstrated resilience by securing domestic support through federal programs like Priority-2030, which allocated nearly one billion rubles in 2025 for research and infrastructure, enabling continued growth in strategic areas.

Terminal Processor Unit

The Terminal Processor Unit (TPU) is a specialized computer-based designed for processing terminal flight data in (ATM) infrastructure, serving as a core component of systems like the FAA's Terminal Automation System. It handles and surveillance inputs to support air traffic controllers in managing aircraft movements near airports. Historically, TPUs emerged in the 1970s and 1980s with the deployment of early automated terminal systems, such as the Automated Radar Terminal System (ARTS) III, which was first commissioned in 1971 to process data for approach and departure control. These systems evolved significantly in the 2000s through the Standard Terminal Automation Replacement System (STARS), initiated in 1996 to replace aging ARTS hardware and software with modern digital processing capabilities. Key functions of the TPU include real-time tracking of within approximately 40-50 nautical miles of , conflict detection to prevent mid-air collisions, integration of weather data for advisories, and generation of displays for controller workstations. In high-volume environments, it can manage up to 1,350 simultaneous tracks, enabling efficient sequencing and separation. Technically, TPUs employ redundant server architectures for , ensuring continuous operation during failures, and interface with primary radars like the Airport Surveillance Radar-11 (ASR-11) as well as multilateration systems for precise positioning. The software supports low-latency to meet demands of terminal operations. Deployed at over 500 U.S. facilities by 2025, including 145 Terminal Radar Approach Control (TRACON) centers and 432 towers, TPUs enhance through automated alerts for potential conflicts and terrain avoidance. International variants appear in EUROCONTROL's systems, such as the ARTAS tracking platform, which performs similar terminal functions. Recent upgrades focus on integrating Automatic Dependent Surveillance-Broadcast (ADS-B) for next-generation surveillance, improving accuracy and capacity while replacing outdated hardware from the 1990s-era ARTS installations. This modernization aligns with broader NextGen initiatives to boost efficiency and reduce delays.