SSD performance is often presented through simple specifications such as sequential read and write speed. However, the actual performance of an SSD depends on much more than its PCIe interface or controller.<\/p>\n
One important factor is NAND flash parallelism<\/strong>.<\/p>\n Inside an SSD, the controller can communicate with multiple NAND flash components through several channels. Each NAND component may also contain multiple dies, allowing the controller to distribute data operations across different internal resources.<\/p>\n This architecture helps determine how efficiently an SSD can process multiple read and write operations at the same time.<\/p>\n Understanding NAND dies, channels, and parallelism<\/strong> can therefore provide a better explanation of why SSDs with similar interfaces and capacities can still deliver different performance.<\/p>\n NAND parallelism refers to the SSD controller’s ability to access multiple NAND resources concurrently or in an interleaved manner.<\/p>\n Instead of processing every operation through a single NAND path, the controller can distribute workloads across multiple channels, dies, and other internal NAND resources.<\/p>\n A simplified SSD architecture can be represented as:<\/p>\n Host System \u2192 SSD Controller \u2192 NAND Channels \u2192 NAND Dies \u2192 NAND Pages<\/strong><\/p>\n The more internal resources that can be effectively used in parallel, the greater the potential for the SSD to process multiple operations efficiently.<\/p>\n However, more NAND resources do not automatically guarantee higher performance. The controller architecture, NAND characteristics, firmware, workload, and overall system design also determine how effectively that parallelism can be used.<\/p>\n These terms are sometimes used interchangeably, but they describe different parts of the SSD architecture.<\/p>\n A die<\/strong> is an individual piece of NAND silicon capable of storing data and performing NAND operations.<\/p>\n A single NAND package can contain one or multiple dies, depending on the NAND design and package configuration.<\/p>\n A NAND package is the physical package mounted on the SSD PCB. It can contain one or more NAND dies.<\/p>\n Therefore, counting visible NAND packages on an SSD does not necessarily tell you the exact number of dies inside the drive.<\/p>\n A channel<\/strong> is a communication path between the SSD controller and NAND devices.<\/p>\n A controller may support multiple NAND channels, allowing it to communicate with different NAND resources in parallel.<\/p>\n This distinction is important because an SSD’s physical NAND package count alone does not describe its internal parallelism.<\/p>\n Consider a simplified SSD with only one NAND channel.<\/p>\n If multiple operations arrive at the same time, the controller has fewer independent communication paths available for distributing those operations.<\/p>\n Now consider an SSD with multiple channels.<\/p>\n The controller can distribute NAND operations across different channels, allowing more work to be handled concurrently.<\/p>\n \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644:<\/p>\n Single Channel<\/strong><\/p>\n Host Requests Compared with:<\/p>\n Multiple Channels<\/strong><\/p>\n Host Requests The second architecture provides more opportunities for parallel NAND access.<\/p>\n This does not mean that every workload will automatically use all available channels. The actual benefit depends on the workload and the controller’s scheduling strategy.<\/p>\n Channels are only one part of the parallelism equation.<\/p>\n Multiple dies within NAND packages can provide additional opportunities for the controller to distribute operations.<\/p>\n For example, a NAND package may contain several dies. The controller can potentially access different dies independently or use interleaving techniques to improve resource utilization.<\/p>\n This creates multiple levels of parallelism:<\/p>\n Channel-Level Parallelism<\/strong> Die-Level Parallelism<\/strong> Plane-Level Parallelism<\/strong> Together, these mechanisms can increase the amount of NAND work that can be processed concurrently.<\/p>\n SSD capacity and internal NAND configuration are closely related.<\/p>\n A higher-capacity SSD generally requires more NAND storage resources. Depending on the NAND generation and configuration, this can provide additional dies or other internal resources that the controller can use for parallel operations.<\/p>\n For example, two SSDs from the same product family may have different NAND configurations at 512GB, 1TB, and 2TB.<\/p>\n The higher-capacity versions may use more NAND dies or different internal organization.<\/p>\n As a result, the performance characteristics of different capacity versions may not scale in a simple linear way.<\/p>\n This is one reason why an SSD’s capacity should not be considered only as a storage-size specification.<\/p>\n Capacity can also influence the internal architecture available for parallel data processing.<\/strong><\/p>\n It is tempting to assume that adding more NAND dies will always make an SSD faster.<\/p>\n In reality, performance depends on how effectively the entire architecture can use those resources.<\/p>\n Several factors are involved:<\/p>\n For example, if a controller has a limited number of channels, adding additional NAND dies does not necessarily create unlimited parallelism.<\/p>\n Similarly, a workload with very low queue depth may not generate enough simultaneous requests to fully utilize all available NAND resources.<\/p>\n Therefore, internal parallelism represents performance potential rather than a guaranteed performance result.<\/strong><\/p>\n Queue depth is another important factor when discussing parallelism.<\/p>\n A storage workload with a queue depth of one generally sends one outstanding I\/O request at a time.<\/p>\n In this situation, the SSD may have fewer opportunities to use its internal resources simultaneously.<\/p>\n At higher queue depths, multiple I\/O requests may be available for the controller to schedule across different NAND channels and dies.<\/p>\n A simplified example:<\/p>\n Low Queue Depth<\/strong><\/p>\n Request \u2192 Controller \u2192 NAND<\/p>\n Higher Queue Depth<\/strong><\/p>\n Request 1 \u2192 Channel 1 The controller has more requests available to distribute across its internal resources.<\/p>\n This is one reason why SSD benchmark results at higher queue depths can look very different from low-queue-depth results.<\/p>\n However, most consumer PC workloads do not continuously operate at extremely high queue depths. For this reason, maximum parallelism is not necessarily the same as maximum real-world responsiveness.<\/p>\n NAND parallelism can affect different workloads in different ways.<\/p>\n Large sequential transfers can provide enough data for the controller to distribute operations across multiple NAND resources.<\/p>\n This can make internal parallelism particularly useful for achieving high throughput.<\/p>\n Random workloads involve smaller and less predictable data requests.<\/p>\n The controller may still use multiple NAND resources, but performance can depend heavily on latency, queue depth, firmware scheduling, and the ability to efficiently locate and access the required data.<\/p>\n Therefore, an SSD with high sequential read\/write performance may not necessarily deliver the same level of improvement in low-queue-depth random workloads.<\/p>\n This is another reason why SSD evaluation should include more than one benchmark metric.<\/p>\n Internal parallelism does not work independently from NAND interface speed.<\/p>\n Even if an SSD has multiple channels and dies, each NAND connection has its own operating limitations.<\/p>\n A newer NAND generation may provide higher interface speeds, while the controller must also be capable of efficiently managing those faster devices.<\/p>\n The final SSD performance therefore depends on the combination of:<\/p>\n NAND Interface Speed \u00d7 Number of Usable Channels \u00d7 NAND Dies \u00d7 Controller Capability \u00d7 Firmware Efficiency<\/strong><\/p>\n This is not a simple mathematical performance formula. Instead, it illustrates that multiple parts of the architecture contribute to the final result.<\/p>\n If one component becomes a bottleneck, additional parallel resources may not provide proportional performance gains.<\/p>\n The SSD controller is responsible for coordinating access to NAND resources.<\/p>\n It needs to manage:<\/p>\n The controller therefore acts as the central coordinator between the host system and NAND flash.<\/p>\n Two SSDs may use similar NAND capacity but different controller architectures, resulting in different levels of effective parallelism and different performance characteristics.<\/p>\n This is why NAND specifications alone cannot fully describe an SSD’s performance.<\/p>\n Having multiple channels and dies provides hardware resources, but firmware determines how those resources are managed.<\/p>\n The firmware decides where data should be placed and how different operations should be scheduled.<\/p>\n For example, when multiple write requests arrive, the firmware can distribute data across available NAND resources to improve utilization.<\/p>\n At the same time, it must consider other operations such as Garbage Collection, Wear Leveling, and SLC cache management.<\/p>\n Poor scheduling can leave some NAND resources underutilized while others become busy.<\/p>\n Effective firmware can therefore help the controller make better use of the available parallel architecture.<\/p>\n Different capacities within the same SSD family may not always use an identical NAND organization.<\/p>\n For example, a 512GB model and a 2TB model may differ in:<\/p>\n As a result, capacity-specific performance testing is important.<\/p>\n An SSD manufacturer should not assume that the performance behavior of one capacity automatically represents every capacity in the same product family.<\/p>\n This is especially relevant for OEM projects where multiple capacity SKUs may be offered under the same product platform.<\/p>\n A product specification may list a maximum sequential read speed such as 3,500MB\/s or 7,000MB\/s.<\/p>\n However, that number does not reveal the complete internal architecture.<\/p>\n Two SSDs may advertise similar sequential performance while using different:<\/p>\n Conversely, an SSD with a theoretically strong internal architecture may not show the same advantage in every workload.<\/p>\n Therefore, benchmark results should be interpreted together with the underlying architecture.<\/p>\n For OEM SSD development, understanding internal parallelism can help determine a more appropriate validation strategy.<\/p>\n Testing can include:<\/p>\n Different Capacity Versions<\/strong><\/p>\n Compare 512GB, 1TB, 2TB, and other capacity configurations individually.<\/p>\n Different Queue Depths<\/strong><\/p>\n Evaluate low-queue-depth and higher-queue-depth performance.<\/p>\n Sequential Workloads<\/strong><\/p>\n Measure how effectively the SSD uses internal resources during large data transfers.<\/p>\n Random Workloads<\/strong><\/p>\n Evaluate performance under smaller and less predictable I\/O requests.<\/p>\n Long-Duration Testing<\/strong><\/p>\n Observe whether performance remains consistent after extended operation.<\/p>\n Thermal Testing<\/strong><\/p>\n Determine whether temperature limits affect the controller’s ability to maintain performance.<\/p>\n The objective is to understand not only the SSD’s maximum performance, but also how effectively its internal architecture works under the target workload.<\/p>\n NAND parallelism is only one part of SSD design.<\/p>\n The final performance of an SSD is influenced by the complete storage architecture:<\/p>\n Host Interface<\/strong> Each layer has its own limitations and performance characteristics.<\/p>\n A balanced SSD design needs to match these components rather than simply maximizing one specification.<\/p>\n More channels without sufficient NAND resources may not provide the expected benefit. More NAND dies without an appropriate controller may also leave some resources underutilized.<\/p>\n The goal is therefore not simply to maximize the number of components, but to create an architecture where the available resources can work efficiently together.<\/p>\n At Oreton, SSD performance is evaluated as a combination of NAND configuration, controller architecture, firmware, interface, thermal behavior, compatibility, and workload requirements<\/strong>.<\/p>\n Different SSD applications may require different balances between capacity, performance, power consumption, and cost.<\/p>\n For OEM projects, capacity-specific configurations also need to be evaluated rather than assuming that one capacity version represents the entire product family.<\/p>\n By considering NAND organization and internal parallelism together with controller and firmware behavior, SSD products can be developed and validated around the actual requirements of the target system.<\/p>\n This approach helps create storage solutions that balance performance, compatibility, stability, quality, and product consistency<\/strong>.<\/p>\n NAND Flash parallelism provides an important link between an SSD’s internal hardware architecture and its actual performance.<\/p>\n Channels<\/strong> provide communication paths between the controller and NAND.<\/p>\n Dies<\/strong> provide additional NAND resources that can be accessed and managed by the controller.<\/p>\n Controller and firmware<\/strong> determine how effectively those resources are scheduled and utilized.<\/p>\n Workload and queue depth<\/strong> determine how much parallelism the host system can actually take advantage of.<\/p>\n For this reason, SSD performance cannot be explained by interface speed or capacity alone.<\/p>\n A better understanding of NAND dies, channels, and internal parallelism provides a more complete view of how an SSD is designed\u2014and why two drives with similar specifications can still behave differently under real workloads.<\/p>","protected":false},"excerpt":{"rendered":" SSD performance is often presented through simple specifications such as sequential read and write speed. However, the actual performance of an SSD depends on much more than its PCIe interface or controller. One important factor is NAND flash parallelism. Inside an SSD, the controller can communicate with multiple NAND flash components through several channels. Each…<\/p>","protected":false},"author":3,"featured_media":4817,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4816","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"yoast_head":"\n1. What Is NAND Flash Parallelism?<\/h2>\n
2. NAND Die, Package and Channel Are Not the Same<\/h2>\n
NAND Die<\/h3>\n
NAND Package<\/h3>\n
NAND Channel<\/h3>\n
3. How Multiple Channels Improve Data Access<\/h2>\n
\n\u2193
\n\u0627\u0644\u0645\u0631\u0627\u0642\u0628 \u0627\u0644\u0645\u0627\u0644\u064a
\n\u2193
\nNAND Channel
\n\u2193
\nNAND<\/p>\n
\n\u2193
\n\u0627\u0644\u0645\u0631\u0627\u0642\u0628 \u0627\u0644\u0645\u0627\u0644\u064a
\n\u2199 \u2193 \u2198
\nChannel 1 | Channel 2 | Channel 3 | Channel 4
\n\u2193 \u2193 \u2193 \u2193
\nNAND | NAND | NAND | NAND<\/p>\n4. The Role of NAND Dies<\/h2>\n
\nMultiple NAND channels can operate independently.<\/p>\n
\nMultiple dies can provide additional NAND resources within the available channels.<\/p>\n
\nSome NAND architectures contain multiple planes within a die, providing additional opportunities for internal operations.<\/p>\n5. Why SSD Capacity Can Affect Internal Parallelism<\/h2>\n
6. More NAND Dies Do Not Always Mean Higher Performance<\/h2>\n
\n
7. Queue Depth and NAND Parallelism<\/h2>\n
\nRequest 2 \u2192 Channel 2
\nRequest 3 \u2192 Channel 3
\nRequest 4 \u2192 Channel 4<\/p>\n8. Sequential and Random Workloads Use Parallelism Differently<\/h2>\n
Sequential Workloads<\/h3>\n
Random Workloads<\/h3>\n
9. NAND Interface Speed Is Also Important<\/h2>\n
10. Controller Design Determines How Parallelism Is Used<\/h2>\n
\n
11. Firmware Turns Hardware Resources Into Usable Performance<\/h2>\n
12. NAND Configuration Can Differ Between SSD Capacities<\/h2>\n
\n
13. Why Peak Speed Alone Does Not Explain SSD Architecture<\/h2>\n
\n
14. NAND Parallelism and SSD Validation<\/h2>\n
15. A Complete SSD Architecture Matters<\/h2>\n
\n\u2193
\nPCIe \/ NVMe<\/strong>
\n\u2193
\nSSD Controller<\/strong>
\n\u2193
\nNAND Channels<\/strong>
\n\u2193
\nNAND Dies \/ Planes<\/strong>
\n\u2193
\nNAND Pages and Blocks<\/strong><\/p>\n16. Oreton’s Approach to SSD Architecture<\/h2>\n
17. Understanding Parallelism Helps Explain Real SSD Performance<\/h2>\n