bundle-multi-4-in-1—python-programming By uplatz<\/a><\/h3>\nArchitecturally, the industry is rapidly moving from board-level pluggable optics to Co-Packaged Optics (CPO), where photonic engines are integrated directly into the same package as the GPU or switch ASIC. This paradigm, championed by industry leaders like NVIDIA with its Spectrum-X and Quantum-X platforms, drastically reduces power consumption, latency, and signal degradation. Looking forward, the evolution continues toward optical I\/O chiplets and 3D-integrated photonic fabrics, which promise to treat high-bandwidth communication as a native function of the chip itself.<\/span><\/p>\nQuantitatively, this shift is delivering unprecedented performance. Bandwidth densities are reaching the terabit-per-second-per-millimeter ($Tb\/s\/mm$) range, and energy efficiency is plummeting from tens of picojoules-per-bit ($pJ\/bit$) for electrical links to the sub-picojoule and even femtojoule-per-bit ($fJ\/bit$) regime for optical solutions. This revolution is not merely an incremental improvement; it is an enabling technology for future computing architectures. Terabit optical interconnects are the critical infrastructure for building massively scaled “AI Factories” with tens of thousands of GPUs, and they are the key to unlocking the potential of disaggregated data centers, where resources like compute, memory, and storage are pooled and composed on demand. This report analyzes the technological underpinnings, competitive landscape, and profound architectural implications of this shift, concluding that the trajectory toward optical I\/O is irreversible and will define the next era of high-performance computing.<\/span><\/p>\n <\/p>\n
Section 1: The Copper Bottleneck: Reaching the Physical Limits of Electrical Interconnects<\/b><\/h2>\n
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The exponential growth in computational demand, driven primarily by large-scale AI models and complex HPC simulations, has exposed a fundamental weakness in modern system design: the physical limitations of electrical interconnects. For decades, the performance of processors like GPUs has scaled in accordance with Moore’s Law, but the copper-based pathways used to shuttle data between them have not kept pace.<\/span>1<\/span> This growing disparity has created a system-level crisis where the ability to move data, rather than the ability to compute it, has become the primary bottleneck. This section dissects the multifaceted failure of electrical interconnects, examining the intertwined challenges of power, bandwidth, signal integrity, and thermal management that necessitate a paradigm shift to an optical solution.<\/span><\/p>\n <\/p>\n
1.1 The Power-Bandwidth-Density Trilemma in Modern GPUs<\/b><\/h3>\n
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Modern GPU architectures are confronted by a “power-bandwidth-density trilemma.” The demand for higher bandwidth to feed thousands of parallel cores requires denser arrays of high-speed electrical links. However, increasing the density and speed of these copper traces inevitably leads to higher power consumption and heat generation, which in turn limits the overall performance and scalability of the system.<\/span>1<\/span> As the industry moves toward multi-core and many-core chip designs, the interconnect network has become a dominant power consumer, projected to account for over 80% of a microprocessor’s total power budget.<\/span>4<\/span><\/p>\nThis escalating power consumption for data movement creates a vicious cycle. The energy required to drive signals through resistive copper traces is converted into heat, exacerbating thermal challenges. To prevent overheating, parts of the chip must be powered down, a phenomenon known as “dark silicon,” which directly limits the computational throughput of the multi-core system.<\/span>4<\/span> Consequently, architects face an intractable trade-off: achieving higher bandwidth with copper necessitates a level of power and heat that the system cannot sustain, creating a hard wall for future performance scaling.<\/span>4<\/span> The problem is not merely about finding a better wire; it is about the architectural unsustainability of using electrons for high-bandwidth data transfer over any significant distance.<\/span><\/p>\n <\/p>\n
1.2 Signal Integrity and Reach Limitations at High Data Rates<\/b><\/h3>\n
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The physical properties of copper present fundamental challenges to maintaining signal integrity at the high frequencies required for modern data rates. As signals travel through electrical traces, they are subject to a host of debilitating effects, including dispersion (where different frequency components of the signal travel at different speeds), attenuation (signal strength loss), ringing, and reflections from discontinuities like vias and connectors.<\/span>1<\/span> These phenomena collectively degrade the signal, increasing the bit error rate and fundamentally limiting both the maximum achievable data rate and the physical distance over which the signal can be reliably transmitted.<\/span><\/p>\nStudies show that while optical signals can travel up to 100 meters with minimal degradation, high-speed electrical interconnects are typically limited to a maximum reach of about 10 meters.<\/span>6<\/span> This limitation is particularly acute in the context of large-scale AI factories, where thousands of GPUs are interconnected across numerous server racks.<\/span>5<\/span> The long cable runs required in such environments make copper-based solutions non-viable. To combat signal degradation over even shorter distances, such as across a motherboard from an ASIC to a front-panel connector, designers must employ complex and power-hungry equalization techniques and Digital Signal Processors (DSPs).<\/span>2<\/span> These components actively compensate for signal distortion but add significant power overhead, cost, and latency to the communication link. For instance, traditional electrical paths in a network switch can incur up to 22 dB of signal loss, making these power-intensive DSPs a mandatory component.<\/span>9<\/span><\/p>\n <\/p>\n
1.3 The Power Delivery Crisis: From 12VHPWR to the Inefficiency of Data Movement<\/b><\/h3>\n
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The challenges of moving electrons at scale are not confined to data signals; they are equally apparent in power delivery. The recent and well-documented issues with the 12VHPWR and its successor, the 12V-2X6 connector, serve as a tangible and dramatic illustration of this crisis.<\/span>10<\/span> These connectors, designed to deliver up to 600W of power to high-end GPUs, have been plagued by incidents of overheating and melting.<\/span>11<\/span> These failures are not merely a flaw in a single connector design but a symptom of the extreme electrical and thermal stresses created by pushing massive currents through dense, compact interfaces.<\/span><\/p>\nThe underlying physics governing this power delivery crisis\u2014current density, electrical resistance, and subsequent heat generation ($I^2R$ losses)\u2014are the same principles that plague high-speed data interconnects. The public failure of power connectors is a leading indicator for the less visible but equally critical failure of electrical data delivery. As data rates climb, the signal traces behave increasingly like power traces, facing similar thermal and integrity challenges. This is reflected in the staggering energy cost of data movement. On a modern processor, performing a 64-bit floating-point operation requires approximately 1.7 pJ of energy.<\/span>13<\/span> In contrast, moving that data over a long on-chip electrical link can cost up to 4 pJ\/bit, and moving it off-chip to main memory can consume as much as 30 pJ\/bit.<\/span>13<\/span> This inversion, where communication is significantly more energy-intensive than computation, underscores the fundamental inefficiency of the current electrical paradigm.<\/span><\/p>\n <\/p>\n
1.4 Thermal Headroom and the Heat Dissipation Challenge<\/b><\/h3>\n
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The high power consumption inherent in electrical interconnects translates directly into a formidable thermal management challenge. The heat generated by resistive losses in cables, connectors, and on-chip traces elevates component temperatures, which can trigger performance throttling, reduce operational lifespan, and increase the risk of outright failure.<\/span>14<\/span> In the dense environment of a data center, this localized heat generation contributes to an enormous system-level cooling burden, which represents a major operational cost.<\/span><\/p>\nThe severity of this thermal wall is evidenced by the industry’s shift towards advanced cooling solutions. The highest-performing systems, including NVIDIA’s forthcoming CPO-based networking switches, are moving away from air cooling and mandating liquid cooling to manage the thermal load.<\/span>9<\/span> This transition, while effective, adds significant complexity and cost to the data center infrastructure. The thermal constraints imposed by electrical interconnects are thus not just a technical inconvenience but a primary driver of system architecture and operational economics, further compelling the search for a more thermally efficient alternative.<\/span><\/p>\n\n\n\n| Metric<\/b><\/td>\n | On-Chip Copper<\/b><\/td>\n | Off-Chip Copper (PCIe Gen5)<\/b><\/td>\n | Advanced Electrical (NVLink 5)<\/b><\/td>\n | Silicon Photonics<\/b><\/td>\n<\/tr>\n\n| Bandwidth Density<\/b><\/td>\n | Medium<\/span><\/td>\n | Low<\/span><\/td>\n | High<\/span><\/td>\n | Very High ($>200\\ Gbps\/mm$)<\/span><\/td>\n<\/tr>\n\n| Max Reach<\/b><\/td>\n | Millimeters<\/span><\/td>\n | $<1$ meter<\/span><\/td>\n | Meters<\/span><\/td>\n | $>100$ meters<\/span><\/td>\n<\/tr>\n\n| Energy Efficiency<\/b><\/td>\n | $0.1-4\\ pJ\/bit$<\/span><\/td>\n | $\\sim10-15\\ pJ\/bit$<\/span><\/td>\n | $\\sim10-20\\ pJ\/bit$<\/span><\/td>\n | $<1-5\\ pJ\/bit$ (goal: $<1\\ pJ\/bit$)<\/span><\/td>\n<\/tr>\n\n| Signal Loss<\/b><\/td>\n | High<\/span><\/td>\n | Very High<\/span><\/td>\n | High<\/span><\/td>\n | Very Low<\/span><\/td>\n<\/tr>\n\n| EMI Susceptibility<\/b><\/td>\n | High<\/span><\/td>\n | High<\/span><\/td>\n | High<\/span><\/td>\n | Immune<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 1: A comparative analysis of key performance metrics for electrical and optical interconnect technologies. Data is synthesized from multiple sources to provide a representative overview.<\/span>1<\/span><\/p>\n <\/p>\n Section 2: Silicon Photonics: The Foundational Shift to Light-Speed Data Transfer<\/b><\/h2>\n <\/p>\n In response to the insurmountable physical barriers of copper, the industry is turning to silicon photonics, a transformative technology that uses light (photons) instead of electrons to transmit data. By fabricating optical components directly onto silicon wafers using mature manufacturing processes, silicon photonics offers a scalable, cost-effective, and high-performance solution to the interconnect bottleneck. This section explores the core principles of this technology, its synergistic relationship with the existing semiconductor ecosystem, and the fundamental components that constitute an on-chip optical communication link.<\/span><\/p>\n <\/p>\n 2.1 Core Principles: Guiding Light on a Silicon Substrate<\/b><\/h3>\n <\/p>\n Silicon photonics is the study and application of photonic systems that use silicon as an optical medium.<\/span>17<\/span> The technology’s operation hinges on two key properties of silicon. First, silicon is transparent to infrared light at the primary wavelengths used for telecommunications (typically around 1.3 \u00b5m and 1.55 \u00b5m).<\/span>17<\/span> Second, silicon has a very high refractive index of approximately 3.5, compared to about 1.44 for its oxide, silica ($SiO_2$).<\/span>17<\/span> This large index contrast is the key to creating highly effective optical waveguides.<\/span><\/p>\nThe standard platform for silicon photonics is the Silicon-on-Insulator (SOI) wafer.<\/span>18<\/span> An SOI wafer consists of a thin layer of crystalline silicon on top of a thicker layer of silica, which itself sits on a standard silicon substrate. By patterning the top silicon layer into narrow channels (waveguides) with sub-micron precision, light can be confined within the high-index silicon core. Due to the principle of total internal reflection at the boundary between the high-index silicon and the low-index silica cladding, the light is guided along the patterned path with very low loss, effectively creating “wires for light”.<\/span>17<\/span> The microscopic dimensions of these waveguides enable the creation of Photonic Integrated Circuits (PICs) with incredible density.<\/span>17<\/span><\/p>\n <\/p>\n 2.2 The CMOS Advantage: Leveraging Decades of Semiconductor Manufacturing Expertise<\/b><\/h3>\n <\/p>\n Perhaps the most significant driver for the adoption of silicon photonics is its compatibility with the existing Complementary Metal-Oxide-Semiconductor (CMOS) manufacturing infrastructure.<\/span>19<\/span> The ability to fabricate PICs using the same lithography, etching, and deposition tools developed and perfected over decades for the electronics industry provides an unparalleled advantage in cost, scale, and reliability.<\/span>21<\/span> This “CMOS advantage” allows for the mass production of complex optical systems at a fraction of the cost of those based on more exotic, specialized materials like Indium Phosphide (InP) or Gallium Arsenide (GaAs).<\/span>21<\/span><\/p>\nHowever, this advantage is a double-edged sword. While leveraging the scale of CMOS makes silicon photonics economically viable, it also imposes the constraints of a process optimized for electronics. Silicon’s fundamental properties, such as its indirect bandgap, make it an inefficient light emitter. This necessitates clever engineering workarounds, such as the heterogeneous integration of other materials onto the silicon platform to create essential components like lasers and high-speed photodetectors.<\/span>20<\/span> Therefore, the story of modern silicon photonics is one of innovative integration, finding ways to augment the silicon platform to overcome its inherent limitations while still benefiting from the foundational CMOS ecosystem.<\/span><\/p>\n <\/p>\n 2.3 Fundamental Components of an On-Chip Optical Link<\/b><\/h3>\n <\/p>\n A complete chip-to-chip optical communication link requires several key components to convert electrical data into light, transmit it, and convert it back into an electrical signal.<\/span><\/p>\n <\/p>\n 2.3.1 Waveguides: The “Wires” for Photons<\/b><\/h4>\n <\/p>\n As the foundational passive component, optical waveguides form the interconnect fabric of a PIC, directing and confining light signals between other components.<\/span>21<\/span> Fabricated from silicon or silicon nitride, these structures are designed to transmit light with minimal propagation loss.<\/span>21<\/span> Their sub-micron dimensions allow for extremely dense routing, and unlike electrical wires, optical waveguides can cross each other in the same layer without interference, significantly simplifying the design of complex circuits.<\/span>27<\/span><\/p>\n <\/p>\n 2.3.2 Modulators: Encoding Data at Terabit Speeds<\/b><\/h4>\n <\/p>\n The optical modulator is the active heart of the transmitter, responsible for encoding a high-speed electrical data stream onto a beam of continuous-wave light. In silicon, the most common modulation mechanism is the free carrier plasma dispersion effect, where applying a voltage to a doped region of silicon changes its refractive index, thereby altering the phase or amplitude of the light passing through it.<\/span>28<\/span> Two primary modulator designs dominate the field, representing a fundamental trade-off between performance and robustness:<\/span><\/p>\n\n- Mach-Zehnder Interferometer (MZI):<\/b> This design splits light into two paths, modulates the phase in one or both paths, and then recombines them, creating constructive or destructive interference to represent data bits.<\/span>29<\/span> MZIs are relatively large and consume more power, but they are thermally stable and can operate over a wide range of wavelengths, making them robust and reliable.<\/span>30<\/span><\/li>\n
- Microring Resonator (MRR):<\/b> An MRR consists of a tiny ring-shaped waveguide placed next to a straight “bus” waveguide.<\/span>28<\/span> At specific resonant wavelengths, light couples from the bus into the ring. By modulating the refractive index of the ring, this resonance can be shifted, effectively turning the light transmission on or off for a specific wavelength.<\/span>28<\/span> MRRs are exceptionally compact\u2014up to 100 times smaller than MZIs\u2014and require very little power to operate.<\/span>31<\/span> However, their performance is extremely sensitive to temperature variations and fabrication imperfections, requiring sophisticated thermal tuning and control circuitry.<\/span>32<\/span><\/li>\n<\/ul>\n
The choice between these designs reflects a core engineering philosophy. The MRR’s pursuit of ultimate density and efficiency is compelling for tightly controlled, co-packaged environments, while the MZI’s robustness is often preferred for less predictable applications. State-of-the-art research is pushing the bandwidth of both types of modulators well beyond 100 GHz.<\/span>28<\/span><\/p>\n <\/p>\n 2.3.3 Photodetectors: Converting Light Back to Electrons<\/b><\/h4>\n <\/p>\n At the receiving end of the link, a photodetector absorbs the incoming photons and generates an electrical current, converting the optical signal back into data that the chip can process.<\/span>20<\/span> Because silicon is transparent at the operating wavelengths, other light-absorbing materials must be integrated into the CMOS process. The two dominant approaches are:<\/span><\/p>\n\n- Germanium (Ge):<\/b> Germanium can be selectively grown on silicon and is an excellent absorber in the 1310 nm and 1550 nm telecommunication bands. Its integration is relatively mature and compatible with CMOS foundry lines, making it a popular choice.<\/span>24<\/span><\/li>\n
- III-V Materials:<\/b> Compound semiconductors like Indium Gallium Arsenide (InGaAs) offer superior absorption coefficients and intrinsic bandwidth compared to Germanium. However, integrating them onto silicon is more complex, typically requiring advanced techniques like die-to-wafer bonding.<\/span>24<\/span><\/li>\n<\/ul>\n
The key performance metrics for photodetectors are high bandwidth (responsiveness), high efficiency (quantum efficiency), and low dark current (noise).<\/span>24<\/span><\/p>\n <\/p>\n 2.3.4 The Laser Challenge: On-Chip vs. External Light Sources<\/b><\/h4>\n <\/p>\n The most significant challenge in silicon photonics stems from silicon’s inability to efficiently generate light due to its indirect bandgap structure.<\/span>21<\/span> This necessitates a solution for providing the light that the modulators will encode. This has led to two distinct architectural approaches:<\/span><\/p>\n\n- External Laser Source (ELS):<\/b> This is the most common and mature approach used in today’s CPO systems.<\/span>29<\/span> A separate, highly efficient and stable laser chip (typically made from InP) is located off the main package. Its light is coupled onto the silicon photonic chip via optical fibers.<\/span>34<\/span> This decouples the thermal and manufacturing challenges of the laser from the PIC but introduces optical coupling losses and increases packaging complexity and cost.<\/span><\/li>\n
- Integrated Lasers:<\/b> The long-term vision is to integrate the laser source directly onto the silicon chip. This is achieved through heterogeneous integration, where III-V gain materials are bonded or grown onto the silicon substrate to form on-chip lasers.<\/span>20<\/span> This approach promises the highest level of integration, lowest power consumption, and greatest density, but it presents formidable challenges in manufacturing yield, thermal management (lasers are highly sensitive to temperature), and reliability.<\/span>20<\/span><\/li>\n<\/ul>\n
<\/p>\n Section 3: Architectural Integration: From Pluggables to Co-Packaged Optics<\/b><\/h2>\n <\/p>\n The theoretical advantages of silicon photonics can only be realized through effective architectural integration with the processing silicon it aims to serve. The industry’s approach to this integration has undergone a rapid and decisive evolution, moving from peripheral, board-level components toward deeply embedded, in-package solutions. This progression is driven by the relentless need to shorten the power-hungry electrical links between the processor and the optical transceiver. This section traces this evolution, focusing on the rise of Co-Packaged Optics (CPO) as the current dominant paradigm and exploring the next frontier of optical I\/O chiplets and 3D integration.<\/span><\/p>\n <\/p>\n 3.1 The Evolution from Board-Level Optics to In-Package Integration<\/b><\/h3>\n <\/p>\n For years, optical communication in data centers has been dominated by pluggable transceiver modules. These modules, installed in cages on the front panel of servers and network switches, convert electrical signals from the main Application-Specific Integrated Circuit (ASIC) into optical signals for transmission over fiber optic cables.<\/span>5<\/span> This architecture was sufficient for data rates up to 100 Gb\/s.<\/span><\/p>\nHowever, as data rates escalated to 400 Gb\/s, 800 Gb\/s, and beyond, the electrical trace on the printed circuit board (PCB) connecting the ASIC to the front-panel module became a severe bottleneck.<\/span>9<\/span> This long electrical path, often spanning several inches, suffers from significant signal degradation and requires substantial power to drive. This inefficiency spurred the imperative to move the point of electrical-to-optical conversion as close as possible to the ASIC, giving rise to in-package integration strategies.<\/span>9<\/span><\/p>\n <\/p>\n 3.2 Co-Packaged Optics (CPO): A Deep Dive into the Dominant Paradigm<\/b><\/h3>\n <\/p>\n Co-Packaged Optics has emerged as the industry’s primary solution to the board-level bottleneck. CPO represents a fundamental shift in system design, moving the optical transceivers from the front panel directly into the same package as the main processing chip.<\/span><\/p>\n <\/p>\n 3.2.1 CPO Architecture: Placing Photonic Engines Beside the ASIC<\/b><\/h4>\n <\/p>\n The core concept of CPO is the heterogeneous integration of one or more optical engines\u2014the Photonic Integrated Circuits (PICs)\u2014and the electronic ASIC on a common substrate within a single package.<\/span>8<\/span> This architecture dramatically shortens the high-speed electrical path from many inches on a PCB to just a few millimeters on the package substrate. This reduction has profound performance implications:<\/span><\/p>\n\n- Reduced Electrical Loss:<\/b> The signal loss is slashed from as high as 22 dB in a pluggable-based system to around 4 dB in a CPO design.<\/span>9<\/span><\/li>\n
- Elimination of Retimers:<\/b> The improved signal integrity eliminates the need for power-hungry DSP-based retimers, which can account for 25-30% of the power in a pluggable module.<\/span>8<\/span><\/li>\n
- Lower Power and Latency:<\/b> The combination of shorter traces and fewer components leads to significant power savings (30-50% or more) and lower overall communication latency.<\/span>8<\/span><\/li>\n<\/ul>\n
<\/p>\n 3.2.2 Case Study: NVIDIA’s Spectrum-X and Quantum-X Photonics Platforms<\/b><\/h4>\n <\/p>\n NVIDIA’s aggressive adoption of CPO for its next-generation networking platforms exemplifies the technology’s importance for AI infrastructure.<\/span>9<\/span> Set to launch in 2026, these platforms integrate silicon photonics engines directly with the switch ASICs.<\/span><\/p>\n\n- NVIDIA Spectrum-X Photonics:<\/b> This Ethernet-based platform is designed for massive AI factories. The flagship SN6800 switch will offer an unprecedented 409.6 Tb\/s of total bandwidth, featuring 512 ports each running at 800 Gb\/s.<\/span>9<\/span><\/li>\n
- NVIDIA Quantum-X Photonics:<\/b> This platform targets InfiniBand networks, with a switch providing 115 Tb\/s of bandwidth across 144 ports at 800 Gb\/s.<\/span>15<\/span><\/li>\n<\/ul>\n
NVIDIA claims these CPO-based systems will deliver a 3.5x reduction in power consumption and a 10x improvement in resiliency compared to traditional pluggable transceiver architectures, directly addressing the critical operational challenges of scaling AI clusters.<\/span>9<\/span><\/p>\n <\/p>\n 3.2.3 Case Study: Broadcom’s CPO Solutions for Switches and XPUs<\/b><\/h4>\n <\/p>\n Broadcom is another key pioneer, already shipping production CPO systems for data center interconnects.<\/span>7<\/span> Their approach demonstrates the immense density gains possible with CPO.<\/span><\/p>\n\n- Tomahawk 5-Bailly Platform:<\/b> This 51.2 Tb\/s CPO solution co-packages a Tomahawk 5 switch ASIC with eight 6.4 Tbps silicon photonics engines on a single substrate.<\/span>7<\/span> This highly integrated design collapses the equivalent of 128 individual 400G pluggable modules into a single device.<\/span>7<\/span><\/li>\n
- Density and Efficiency:<\/b> Broadcom reports that this CPO architecture achieves an 8x improvement in silicon area efficiency for the photonics compared to their PICs used in pluggable modules.<\/span>7<\/span> The company is already testing its fourth-generation CPO technology, which will deliver 400G per lane and a total bandwidth of 104.2 Tbps.<\/span>40<\/span><\/li>\n<\/ul>\n
<\/p>\n 3.3 The Next Frontier: Optical I\/O Chiplets and 3D Integration<\/b><\/h3>\n <\/p>\n While CPO is a significant leap forward, it is an intermediate step. The ultimate goal is to treat optical I\/O not as a separate component to be packaged alongside a chip, but as a fundamental, integrated part of the chip itself. This vision is being realized through optical I\/O chiplets and advanced 3D packaging. This approach represents a more profound architectural shift, moving photonics from a system-level integration problem into the domain of standard chip design, thereby democratizing the technology for wider adoption.<\/span><\/p>\n <\/p>\n 3.3.1 Ayar Labs and the TeraPHY Chiplet Approach<\/b><\/h4>\n <\/p>\n Ayar Labs is at the forefront of the optical I\/O chiplet movement.<\/span>31<\/span> Their flagship product, the TeraPHY\u2122, is a fully integrated electro-optical transceiver on a small die, designed to be co-packaged with processors like GPUs or CPUs using standard multi-chip module techniques.<\/span><\/p>\n\n- Performance:<\/b> A single TeraPHY chiplet can deliver up to 2 Tbps of bidirectional bandwidth. This translates to an I\/O bandwidth density of 200 Gbps per millimeter of the host chip’s edge, a 1000x increase over what is possible with electrical I\/O.<\/span>5<\/span><\/li>\n
- Ecosystem:<\/b> Critically, Ayar Labs has designed its chiplet to be compatible with the Universal Chiplet Interconnect Express (UCIe) standard.<\/span>31<\/span>
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