Figure 1. Acacia’s Wall of Patents.

A recent Gazettabyte article details how our co-founders carried out this mission, introducing improvements in performance and power consumption to legacy coherent technology, initially used for the most challenging optical transmission links. Looking through our history, it’s clear to see the trailblazing path Acacia helped to define with coherent optical modules, especially pluggable modules. Acacia has always been laser-focused on providing customers with continuous improvements in speed, capacity, performance, size, and power consumption to meet the ever-growing demand for bandwidth. This has been done by focusing on (1) silicon-based optical and electrical designs, (2) advanced digital signal processing (DSP), (3) high-speed RF expertise, and (4) volume manufacturable high-density packaging, with all these disciplines “under one roof.” As a result, Acacia is now a leading supplier of coherent modules with multiple product families to support speeds from 100G to 1.2T, including a broad portfolio of 400G and 800G pluggable products, to address the needs of network operators worldwide.

Pioneer of Coherent Pluggables
It is interesting to note that this year marks the 30th anniversary of a significant event in optical transceiver history. It was in 1995 when the first standards-based pluggable optical transceiver called the Gigabit Interface Convertor (GBIC) was first defined, with supported speeds up to ~1Gbps. It was ~20 years from this achievement that Acacia introduced the first optical coherent pluggable transceiver to support 100Gbps in the multi-source agreement (MSA) CFP form factor.

Figure 2. Industry standardized pluggable modules: From the early days of 1G GBICs to today’s coherent pluggables capable of 3000km+ 400G and 1000km+ 800G.

And today, Acacia’s latest generation of coherent pluggable modules powered by the Delphi DSP, our 9th generation DSP, has enabled extraordinary reaches using even smaller QSFP-DD and OSFP form-factor modules. Acacia’s 400G ultra long-haul modules support distances beyond 3000km, and 800G ZR+ enhanced performance modules support distances beyond 1000km.

Leadership in Industry Standards
To ensure a thriving marketplace for coherent pluggable optics, many companies participate in MSA initiatives and/or in industry standards groups to agree on module product requirements to ensure a multi-vendor supply, interoperability, and economies of scale. Acacia has been a key driver and participant in many of these organizations. In the 400G pluggable generation, Acacia served as editor for the 400ZR Implementation Agreement in OIF. Acacia was also a founding member of the OpenZR+ MSA, which provided requirements for enhanced performance 400ZR+ with multi-vendor interoperability. Market adoption of 400ZR and OpenZR+ solutions has been the fastest of any coherent technology in history.

In the 800G pluggables generation, Acacia has continued its leadership in industry standards activities. As a key contributor along with other coherent suppliers, Acacia introduced the first standardized, interoperable probabilistic constellation shaping (PCS) mode for 800G ZR+ enhanced performance, enabling network operators to expand their 800G reaches beyond 1000km. The company is also playing a key role in driving 1600ZR/ZR+ industry agreements.

With the increasing demand for the current generations of 400G and 800G coherent pluggable modules, several companies have jumped on the bandwagon to participate in this optical renaissance. These 400G and 800G QSFP-DD and OSFP form-factor modules, capable of plugging directly into switch and router ports, have invigorated architectures using router-based coherent optics as a networking solution to reduce overall total cost of ownership.

Silicon-based Designs, Advanced DSPs, and High-Density Packaging
The key to Acacia becoming a market leader in coherent optics stems from our ongoing focus on core technology. For example, an important factor that provided many advantages in low power and high-density packaging was Acacia’s adoption of silicon photonics for high-speed coherent transmission. Silicon does not require temperature stabilization, which results in lower power implementation. In addition, silicon photonics can leverage high-volume CMOS packaging techniques to reduce overall cost. Our design and development approach has always been to utilize silicon photonics for both MSA pluggable modules as well as performance-optimized modules, providing design and operational efficiencies as well as rapid time to market. Following Acacia’s lead, we are now seeing multiple suppliers also embracing silicon photonics technology in their coherent pluggable modules because of the benefits it has delivered to the industry.

Another key technology advantage that sets Acacia apart is its coherent DSP design and capabilities. Innovation in this area has been critical for mitigating impairments such as dispersion and non-linear effects incurred during transmission over optical fiber. Acacia’s balanced and power-efficient approach to DSP development ensures robust algorithms while minimizing power consumption. As CMOS node sizes continue to shrink, relatively complex techniques for improving performance can be introduced into very compact MSA pluggable modules. The improved performance is enabling network operators to expand the types of architectures they can deploy using these pluggables, resulting in the ability to offer a wider range of network applications.

Driving innovation to meet increasing transmission baud rates meant having in-house cross-disciplinary teams to ensure the best designs. We were able to achieve this while also delivering a compact low power consumption device. Acacia’s 3D Siliconization enabled this high-density level of packaging with high signal integrity and allowed us to also leverage volume manufacturable processes used in the electronics industry. This approach enabled faster scaling of manufacturing and improved reliability.

15+ Years of Industry Firsts and Design Expertise
Technology leadership is a culmination of many factors, not just having the expertise in the technology itself. It is comprised of how the technology is developed and quickly brought to market with the capability of volume while maintaining quality, and with the goal of meeting customer requirements. Many factors have contributed to Acacia’s technology leadership, including an engineering approach based on in-house design expertise across key disciplines, leveraging years of experience, building on the successes of previous generations as well as adjacent industry innovations and manufacturing processes, and participating in industry standards. This powerful combination created many industry firsts over the last 15+ years since Acacia was founded.

Figure 3. Acacia has achieved many industry firsts for coherent pluggable modules since its founding.

Acacia has introduced coherent module products, including its recent Delphi-based pluggable modules, leveraging nine generations of DSP ASICs, and holds an industry leadership position when it comes to innovative design, quality, and manufacturability of coherent pluggable modules especially as baud rates increase while size and power consumption requirements decrease. Acacia continues to demonstrate its technology leadership as we move to higher bandwidth applications such as AI, as well as customer requirements for higher speed solutions such as 1600G MSA pluggable modules.

Market Adoption and Use Case Expansion
Coherent pluggables have seen remarkable market adoption, with 400G ZR/ZR+ coherent optics becoming the most widely adopted coherent technology in history. While some in the industry predicted early on that 400ZR pluggables would only be a small portion of the coherent market, Acacia has been laser focused on bringing these solutions to its customers to deliver the architectural change needed to transform networks to meet ever-growing bandwidth demands. As a result, Acacia is a market leader in shipments of 400G+ coherent pluggables.

During 2024, Acacia expanded this market-leading portfolio with the introduction of 800ZR and 800G ZR+ pluggables with Interoperable PCS in QSFP-DD and OSFP form factors. These solutions have already been proven in field trials, with Colt being the first provider to successfully trial enhanced performance 800G ZR+ coherent pluggable optics. These 800G router-based optics provide the capability to double Colt’s packet core capacity per link while reducing power per bit by 33.3%.

Acacia also introduced a 400G Ultra Long Haul QSFP-DD module for expanding 400G applications from DCI/metro to long haul applications. The 400G UHL has been proven in field trials, with Arelion announcing that it completed a live network field trial on its route from Chicago to Denver that demonstrated successful IP transmission at a spectrum of 112.5 gigahertz over 2,253 kilometers, with healthy margins, providing longer transmission distances and greater cost savings than currently deployed transponders. Acacia’s 400G ULH pluggables enable Arelion to reduce CAPEX by 35 percent and OPEX costs by 84 percent when expanding its network, providing wider reach with high capacities that support customers’ AI/ML and cloud applications.

The Terabit Era is Going Strong
According to Cignal AI, in 2025, 1.2T+ performance optimized solutions will contribute significantly to bandwidth growth as those solutions continue to be introduced. Acacia’s 1.2T Coherent Interconnect Module 8 (CIM 8), powered by the Jannu DSP, has proven its outstanding performance with multiple record-breaking field trials across Metro, Long Haul and Subsea with Microsoft, Verizon, Windstream, and others. Acacia is also engaged with multiple webscale customers and expects CIM 8 to continue its ramp in 2025.

Looking Ahead…..Artificial Intelligence, 1600ZR/ZR+ and More!
AI certainly was a hot topic during OFC and ECOC in 2024 and Acacia believes it will continue to be in 2025. While a year ago, the industry was focused on single-site AI clusters, we will begin to hear more about methods for distributing AI training over different locations in 2025. And while there is still a lot of work to happen in this area, the optics industry is well positioned to be at the forefront of this evolution since higher speed optical interconnections will be necessary to mitigate bandwidth constraints within an AI networks. Read this recent blog for more information on future proofing your network for AI.

Router-based Coherent Optics
The proliferation of router-based coherent optics is paving the way to a converged IP+Optical network architecture. The benefits in 2024 were clear. Infrastructure provider Colt Technology Services reported a stunning 97% energy savings, and Arelion saved 64% in CapEx and 76% in OpEx. In 2025, we can expect to see more providers leveraging this architecture to achieve increased capacity, reduced energy consumption, and lowered network costs, complexity, and footprint.

1600ZR and 1600ZR+ Standards Agreement
The OIF launched efforts last year on 1.6T coherent optical interconnect solutions and is making progress towards interoperable 1600ZR and 1600ZR+ implementation agreements.  In 2025, the industry will be looking at ways to advance this migration using advanced technologies for high baud rate modulation and smaller CMOS nodes.

Looking to the Future
Acacia is looking forward to another year of industry-wide innovation. Helping to solve some of our customers’ most challenging problems has been part of our DNA since Acacia was founded in 2009 and as you can see from this historic timeline, we have continued to set new benchmarks for performance and efficiency. These innovations are not only addressing the current demands of high capacity networks, but are also paving the way for future growth and scalability. Key to this success has been listening to our customers and designing the products and features that they need to be successful. We look forward to continuing that tradition.

The Optical Internetworking Forum (OIF) kicked off the 400G MSA pluggable generation with development of the 400ZR implementation agreement enabling point-to-point amplified links up to 120km operating at 60+Gbaud data rates. Around the same timeframe, the OpenROADM MSA defined 400G interfaces for ROADM networks and extended reaches; the OpenZR+ MSA leveraged these higher performance interfaces to enable interoperable enhanced performance links for 400G pluggable modules (Figure 1).

The introduction of high-transmit optical power (>0dBm) ZR+ modules such as Acacia’s Bright 400ZR+ module further expanded the 400G MSA pluggable space to include brownfield ROADM network architectures (with existing transponder channels ~0dBm). Driven by increasing bandwidth demands from applications such as AI, network operators are now looking towards a new generation of MSA pluggable products that further expand applicable networking scenarios that operators can leverage to scale and meet these demands.

How Industry Standards Benefit MSA Pluggable Module Adoption
The latest array of MSA pluggable products introduces a new set of capabilities that network operators can utilize to increase capacity and extend reach. These products provide the ability to deploy 800G with ZR, ZR+, and high-transmit optical power capabilities, as well as extending the capabilities of existing 400G router interfaces to support ultra-long-haul (ULH) reach capabilities. This new generation of modules continues to leverage industry standardization while also borrowing capabilities from performance-optimized coherent solutions. These capabilities include high-baud rate transmission allowing for a doubling of baud rates from the previous Class 2 (~60+Gbaud range) generation to Class 3 (~120+Gbaud range) baud rates, the use of probabilistic constellation shaping (PCS) for enhanced transmission performance, and L-band support for spectrum range expansion.

Figure 1.  Interoperability approaches at 400G vs. 800G.

Industry standardization of coherent solutions plays a key role in enabling economies of scale. Users of 400G coherent MSA pluggable modules such as 400ZR/ZR+ have benefited from the efforts of OIF, OpenZR+ MSA, and OpenROADM MSA to provide industry agreements on module specifications resulting in a diverse supply base. We have seen similar efforts to garner industry standardization as users transition to 800G MSA pluggables. There are three main elements that differentiate 800G relative to 400G and are adapted from previously developed performance-optimized solutions.

1. Interop PCS for Enhanced Performance
   A key difference between 400G and 800G interoperability approaches for an enhanced performance “ZR+” is that instead of using enhanced performance forward error correction, oFEC, to provide improved 400G performance, 800G uses industry standard interoperable probabilistic constellation shaping (PCS) for enhancing performance. PCS is a transmission shaping technique that provides additional link performance beyond traditional transmission modes such as 16QAM. Industry standardization of an interoperable PCS transmission shaping function, once relegated to proprietary performance-optimized transponder platforms including those for submarine applications, is a tremendous leap forward in the progress of MSA pluggable module capabilities. Multi-vendor 800G module supply chain diversity from a DSP ASIC perspective is possible when the 800G ZR+ performance enhancement mode utilizes the industry standard interoperable PCS mode.
2. High Baud Rate Design
   PCS is not the only technology that has been adapted from performance-optimized solutions for MSA pluggables. 800G as well as a 400G ULH pluggable solutions require a high-baud rate design operating in the Class 3 ~120+ Gbaud data rate range. Acacia’s performance-optimized CIM 8 module capable of 140Gbaud speeds has already proven that its deployed technology far exceeds the requirement for the new generation of MSA pluggables. Operation at these high baud rates benefits heavily from the advanced integration and RF signal optimization techniques that Acacia introduced in our 400G MSA pluggable product family.

Figure 2.  Tightly integrated components enable 120+Gbaud data-rate capabilities.

3. C & L Band Support
A third element of the latest 800G MSA pluggable generation that is borrowed from performance-optimized designs is the capability to transmit in the L-band wavelength range, in addition to the traditional C-band DWDM range. By adding L-band supporting infrastructure to a network, the network capacity is approximately doubled. Network operators now have an option beyond utilizing a transponder platform if they wish to use L-band expansion to increase network capacity.

Figure 3.  New generation of coherent MSA pluggable modules to take advantage of L-Band transmission window, adding to existing C-Band support.

Pluggable Interoperable Interfaces are Driving Adoption of 800G Modules
Acacia’s latest family of coherent solutions are powered by its 9th generation DSP ASIC called Delphi. These modules include support for OIF 800ZR, interoperable 800G ZR+ using the OpenROADM interop PCS mode, and 400G ULH for ultra-long-haul reaches. These modules utilize Acacia’s 3D Siliconization providing a highly integrated design enabling high-baud rate modulation. With support for QSFP-DD and OSFP form factors, as well as >+1dBm transmit optical power and L-band support, Acacia’s Delphi generation of products leverage the deployment successes of our performance-optimized CIM 8 module to provide MSA pluggable products that offer increased capacity and longer reaches.

Figure 4.  Acacia’s latest generation of MSA pluggable 800G and 400G ULH modules.

Similar to the successful path we saw 400G pluggables experience, these modules are delivering the performance and interoperability that is critical for driving economies of scale and widespread adoption. With data center bandwidth continuing to grow rapidly, fueled by emerging new applications such as AI, these high-performance pluggable modules are on track to become an important tool for network operators to cost-efficiently scale their networks to meet this surging demand.

See Us at ECOC 2024!
Acacia is excited to be participating in the OIF interoperability demo at ECOC 2024 showcasing both its 400G and 800G pluggables; demos will take place in the OIF booth #B83. Acacia will also be demonstrating the Interoperable 800G ZR+ module in our meeting room at ECOC. Click here to set up a meeting.

We hope to see you in Frankfurt!

While the near-term focus has been on how AI will affect the technology around short reach interconnects, there will certainly be an impact to interconnections beyond the AI clusters and beyond the AI data center, in hyperscaler networks.

The question is:  beyond the short-distance high-bandwidth interconnections, how would AI traffic impact the optical transport environment beyond the intra-building network and into the metro, long haul, and longer reach applications where optical coherent transmission is heavily utilized?

Figure 1.  Sales Forecast for Ethernet Optical Transceivers for AI Clusters (July 2024 LightCounting Newsletter, “A Soft Landing for AI Optics?”).

Effect of Past Applications on the Transport Network
Bandwidth-intensive computing is attributed to both AI training as well as AI inference, where inference refers to the post-training process in which the model is “ready for the world,” creating an inference-based output from input data using what it learned during the training process. In addition to AI training’s requirements for a large amount of computing power and a large number of high-bandwidth, short connections, there are also foreseen bandwidth requirements beyond the AI data center. To understand how network traffic patterns may evolve beyond the AI data center, let’s review some examples of how the wider transport network was affected by past growth of various applications. Although these applications may not strongly match the effect of AI application traffic, it can provide some insight into the effects that the growth of AI applications may have on optical transport, and thus on the growth of coherent technology.

If we look at search applications, the AI training process is generally analogous to a search engine’s crawling bots combing the internet to gather data to be indexed (AI training being much more computationally intensive). The AI inference process is analogous to the search engine being queried by the end user with results made available for user retrieval with minimal latency. While the required transport bandwidth for search bots and user queries are minimal compared to higher bandwidth applications, the cumulative effect of the search-related traffic is part of the contribution to overall transport traffic, including bandwidth from regional/local caching to minimize latency, as well as usage from subsequent traffic created by acting upon search results.

Understanding how network traffic was affected by the growth of video content delivery is another example that can inform potential AI network transport traffic patterns. A main concern resulting from video content distribution was the burden imposed on the network in delivering the content (especially high-resolution video) to the end-user. To address this concern, content caching, where higher demand content was cached closer to the end-user, was implemented to reduce overall network traffic from the distribution source to the end-user, as well as reduce latency. While it is too early to predict how much network traffic would increase due to expansive queries to and responses from AI inference applications, the challenge is to ensure the latency for this access is minimal. One could see an analogy of content caching to edge computing where the AI inference model is closer to the user with increased transport bandwidth required for these edge computing sites. However, the challenge would be to understand how this would affect the efficiency of the inference function.

Turning to cloud computing for insights on traffic patterns, the rise of (multi-) cloud and computing resulted in intra and inter-datacenter traffic (a.k.a. east-west traffic) increasing as workloads traversed across the datacenter environment. There’s a similar potential rise in this type of traffic with AI as data for training could be dispersed among multiple sites of clusters as well as inference models being distributed to physically diverse sites to reduce latency to end users.

For any of these previous examples, as the demand of these applications increases, the transport bandwidth requirements would also increase from not only the target data (e.g., search results, video), but also from overhead or intra datacenter traffic to support these applications (e.g., content caching, cloud computing, backend overhead). Traffic behavior for aggregating AI training content as well as the distribution of AI inference models and its results may be similar to the traffic patterns of these previous applications, applying pressure to network operators to increase capacity for its data center interconnect, metro, and regional networks. Long haul and subsea networks may also experience a need to expand to meet the demands of AI-related traffic.

Figure 2.  A scenario in which the network fabric physically expands due to facility power constraints, requiring high-capacity optical interconnections.

The Balance of Power and Latency
While the application examples above are related to how the AI application itself may affect bandwidth growth, what is becoming apparent is the power requirements to run AI clusters and data centers are significant. In the past, as the demand for cloud services grew, the need for large-scale data centers to have access to localized inexpensive power sources helped to drive the location selection for large data centers. However, power facility/availability constraints helped drive the adoption of physically distributed architectures, which then relied on high-capacity transport interconnects between data centers to maintain the desired network architecture (Figure 2). We anticipate a similar situation with AI buildouts requiring distributed facilities to address power constraints with potential trade-offs of reduced efficiencies for both AI training and inference. The distributed network would then rely on high-capacity interconnect transport using coherent transmission to extend the AI network fabric. Unlike cloud applications, physical expansion of the network fabric for AI applications has a different set of challenges due to compute and latency requirements for both training and inference.

Figure 3. Extremely low latency is required within the AI cluster to expeditiously process incoming datasets during the training mode. Since datasets are collected before being fed into the training cluster, the process of collecting these datasets may not be as latency sensitive.

As we plan for AI buildouts, one common question is how the physical extension of an AI networking fabric may affect AI functions. While geographic distribution of AI training is not ideal, facility power constraints are certain to lead to a growing adoption of distributed AI training techniques that attempts to mitigate introduced latency effects. As part of the training process, sourcing datasets feeding into the training cluster may not be latency sensitive and would not be as impacted by physical network extension (Figure 3). After training, when the inference model is complete, the goal is to minimize the latency between the user query to the inference model and the transmitted results to the user (Figure 4). The latency is a combination of the complexity of the query as well as the number of “hops” between the inference model and the user. Latency reduction when accessing the inference model, as well as methods to effectively distribute both the training and the inference function beyond a centralized architecture to address single-site power constraints, are ongoing discussions within the industry.

Whether driven by power constraints, dataset sourcing, or inference response efficiency, the sheer growth of AI applications will drive network traffic growth beyond AI cluster sites towards the wider network requiring high-capacity interconnects.

Figure 4.  Minimizing latency for AI inference is a key objective.

Trading off power requirements versus access to inexpensive and abundant power versus latency is familiar territory when it comes to bandwidth intensive applications. The outcome that optimizes these trade-offs is application dependent and can even be deployment-by-deployment dependent. We continue to watch the evolving AI space to see how these network architecture trade-offs will play out, with the impact of how the transport network is designed. High-capacity coherent transport can certainly influence these trade-offs. And as we have already seen, by using coherent high-capacity transport cloud architectures, networks were able to physically expand to alleviate power source constraints by provided fat-pipe links between sites. We anticipate a similar scenario with expanding AI network architectures.

The Ripple Effect
While the near-term focus on high-capacity interconnects for AI applications has been on short reach connections within AI clusters, we are already seeing bandwidth requirements begin to increase, requiring additional coherent connectivity between datacenters supporting AI. And while there is general agreement that the resulting bandwidth demand from AI applications translates to increased traffic across the network, we are at the early stages in understanding how specific segments of the network are affected. Coherent optical interconnects for high-capacity transport beyond the data center already provide performance-optimized transponder solutions at 1.2T per wavelength as well as 400G router-to-router wavelengths moving to 800G using MSA pluggable modules. This technology will continue to play a role in the transport solution supporting AI applications whether the expanding traffic is in the metro portion, data center interconnects, long haul, or beyond.