{"id":2816,"date":"2026-02-24T08:30:00","date_gmt":"2026-02-24T01:30:00","guid":{"rendered":"https:\/\/dgway.com\/blog_E\/?p=2816"},"modified":"2026-02-27T08:40:47","modified_gmt":"2026-02-27T01:40:47","slug":"from-1600-mb-s-to-6300-mb-s-how-we-can-achieve-incredible-file-system-performance","status":"publish","type":"post","link":"https:\/\/dgway.com\/blog_E\/2026\/02\/24\/from-1600-mb-s-to-6300-mb-s-how-we-can-achieve-incredible-file-system-performance\/","title":{"rendered":"From 1600 MB\/s to 6300 MB\/s: How we can achieve incredible file system performance?"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In traditional FPGA-based Embedded Linux systems, NVMe storage performance typically stalls at <strong>~1,600 MB\/s<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Why?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Because most MPSoCs rely on:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>PCIe Gen3 Hard IP<\/li>\n\n\n\n<li>Standard Linux NVMe drivers<\/li>\n\n\n\n<li>Software-based protocol processing<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The result? A serious performance bottleneck that prevents modern Gen4 SSDs from reaching their true potential.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But what if embedded platforms could break that limit?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Today, we demonstrate <strong>6,300 MB\/s sustained file system write performance<\/strong> on a Linux-based AMD Zynq UltraScale+ MPSoC platform \u2014 fully validated, reproducible, and tested with real hardware.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">\ud83c\udfa5 Watch the Full Demonstration<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">See the live benchmark comparison (fio vs. io_uring-perf) and full system architecture explanation here:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\ud83d\udc49 <a href=\"https:\/\/youtu.be\/JR-iV7MUH8E\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>YouTube Demo<\/strong><\/a><\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"From 1600 MB\/s to 6300 MB\/s: Four Keys to high performance NVMe File Access on FPGA based Linux\" width=\"680\" height=\"383\" src=\"https:\/\/www.youtube.com\/embed\/JR-iV7MUH8E?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udd0d The Bottleneck in Conventional Systems<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Using:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>PCIe Gen3 Hard IP<\/li>\n\n\n\n<li>Standard Linux NVMe driver<\/li>\n\n\n\n<li>Software-heavy I\/O handling<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">File-level write performance is typically capped at around <strong>1,600 MB\/s<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Even when switching to PCIe Gen4 SSDs, the system architecture becomes the limiting factor.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To break this barrier, optimization must happen <strong>end-to-end<\/strong> \u2014 from hardware interface to application layer.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udd11 The Four Keys to 6,300 MB\/s<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Achieving 6.3 GB\/s file-system throughput requires coordinated optimization across four layers:<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"256\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/The_Four_Keys_to_breaking_the_limit-1-1024x256.jpg\" alt=\"Diagram illustrating the four key technologies behind achieving 6,300 MB\/s file system performance on embedded Linux: PCIe Gen4 Soft IP, rmNVMe-IP hardware offload engine, dual-channel DMA architecture, and optimized io_uring application for high-throughput NVMe SSD acceleration in data center environments.\" class=\"wp-image-2829\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/The_Four_Keys_to_breaking_the_limit-1-1024x256.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/The_Four_Keys_to_breaking_the_limit-1-300x75.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/The_Four_Keys_to_breaking_the_limit-1-768x192.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/The_Four_Keys_to_breaking_the_limit-1-1536x384.jpg 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/The_Four_Keys_to_breaking_the_limit-1.jpg 1920w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Four Keys to Achieving 6300 MB\/s on Embedded Linux<\/figcaption><\/figure>\n<\/div>\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">1\ufe0f\u20e3 PCIe Gen4 Soft IP Embedded in rmNVMe-IP<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Standard Adaptive SoCs do not provide PCIe Gen4 Hard IP.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">By integrating <strong>PCIe Gen4 Soft IP directly inside rmNVMe-IP<\/strong>, we unlock:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Full Gen4 bandwidth<\/li>\n\n\n\n<li>~7,000 MB\/s raw capability<\/li>\n\n\n\n<li>Removal of Gen3 hardware bottleneck<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This enables true Gen4 SSD performance on embedded FPGA platforms.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">2\ufe0f\u20e3 Full Hardware Offload Architecture<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Traditional Linux NVMe drivers process much of the NVMe and PCIe stack in software.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Our solution:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Offloads NVMe protocol handling to hardware<\/li>\n\n\n\n<li>Minimizes CPU overhead<\/li>\n\n\n\n<li>Reduces latency<\/li>\n\n\n\n<li>Improves queue efficiency<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The rmNVMe-IP architecture shifts protocol processing away from the CPU and into programmable logic \u2014 where it belongs for high-throughput systems.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">3\ufe0f\u20e3 Dual-Channel High-Speed DMA (PS \u2194 PL Bridge)<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">To match external Gen4 bandwidth internally, we designed:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Dual 128-bit AXI interfaces<\/li>\n\n\n\n<li>Custom 256-bit aligned DMA engine<\/li>\n\n\n\n<li>1MB max I\/O transfer size<\/li>\n\n\n\n<li>256 hardware queue tags per queue<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This allows the system to sustain over <strong>8,000 MB\/s internal data bandwidth<\/strong>, preventing internal congestion.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">4\ufe0f\u20e3 High-Performance Application Using io_uring<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Even optimized hardware can be limited by inefficient applications.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Standard benchmark tools like <code>fio<\/code> reached:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>~4,000 MB\/s (filesystem write)<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">But our custom application built on <strong>io_uring<\/strong> achieved:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\ud83d\udc49 <strong>6,300 MB\/s sustained file-system write throughput<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Why?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Because io_uring enables:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Asynchronous submission\/completion rings<\/li>\n\n\n\n<li>Batch I\/O<\/li>\n\n\n\n<li>Zero-copy data paths<\/li>\n\n\n\n<li>Reduced system calls<\/li>\n\n\n\n<li>Lower context switching<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The result: maximum throughput with minimal CPU overhead.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udcca Real Performance Results (Validated on ZCU106 + Intel P5800X)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Raw Device (Gen4)<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Sequential Write (fio): ~4,183 MB\/s<\/li>\n\n\n\n<li>Sequential Write (io_uring-perf): ~6,303 MB\/s<\/li>\n\n\n\n<li>Sequential Read: ~5,359 MB\/s<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Filesystem (ext4)<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Sequential Write (fio): ~4,126 MB\/s<\/li>\n\n\n\n<li>Sequential Write (io_uring-perf): ~6,165 MB\/s<\/li>\n\n\n\n<li>Mixed R\/W: ~2,613 MB\/s sustained<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These are not simulation results. They are measured, reproducible, and fully documented.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83c\udf0d Why This Matters for Data Storage &amp; Data Centers<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Breaking the 1,600 MB\/s barrier transforms embedded platforms into serious data infrastructure nodes.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u2714 AI Video Analytics<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Sustain multi-channel 4K\/8K recording without frame loss.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"616\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/AI_Video_Analytics-1024x616.jpg\" alt=\"Diagram showing multi-channel 4K and 8K cameras streaming high-bandwidth video data into an FPGA + Linux system for real-time processing, simultaneous video streaming, and sustained SSD recording\u2014demonstrating 6,300 MB\/s file system performance for AI video analytics without frame loss.\" class=\"wp-image-2824\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/AI_Video_Analytics-1024x616.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/AI_Video_Analytics-300x180.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/AI_Video_Analytics-768x462.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/AI_Video_Analytics-1536x924.jpg 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/AI_Video_Analytics.jpg 1540w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">AI Video Analytics on FPGA + Linux<\/figcaption><\/figure>\n<\/div>\n\n\n<h3 class=\"wp-block-heading\">\u2714 5G \/ MEC Infrastructure<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">High-speed packet logging and edge CDN caching.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"616\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/5G_MEC_Infrastructure-1024x616.jpg\" alt=\"Illustration of 5G MEC infrastructure showing edge servers, CDN edge computing, and virtualized network functions connected to a 5G tower\u2014representing high-speed packet logging and real-time edge CDN caching enabled by 6,300 MB\/s NVMe file system performance.\" class=\"wp-image-2825\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/5G_MEC_Infrastructure-1024x616.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/5G_MEC_Infrastructure-300x180.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/5G_MEC_Infrastructure-768x462.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/5G_MEC_Infrastructure-1536x924.jpg 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/5G_MEC_Infrastructure.jpg 1540w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">5G \/ MEC Infrastructure<\/figcaption><\/figure>\n<\/div>\n\n\n<h3 class=\"wp-block-heading\">\u2714 Industrial Data Acquisition<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Continuous high-frequency sensor capture.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"616\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Industrial_Data-_Acquisition-1024x616.jpg\" alt=\"Illustration of an industrial high-speed data acquisition system capturing continuous high-frequency sensor signals and streaming them to SSD storage\u2014demonstrating sustained 6,300 MB\/s file system performance for real-time industrial monitoring and edge analytics.\" class=\"wp-image-2826\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Industrial_Data-_Acquisition-1024x616.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Industrial_Data-_Acquisition-300x180.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Industrial_Data-_Acquisition-768x462.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Industrial_Data-_Acquisition-1536x924.jpg 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Industrial_Data-_Acquisition.jpg 1540w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Industrial Data Acquisition<\/figcaption><\/figure>\n<\/div>\n\n\n<h3 class=\"wp-block-heading\">\u2714 Edge Databases<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Stable, predictable high-throughput storage without I\/O bottlenecks.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"616\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Edge_Database__Analytics-1024x616.jpg\" alt=\"Illustration of a high-performance edge database architecture with distributed nodes and analytics dashboards, representing stable and predictable 6,300 MB\/s NVMe file system performance that eliminates I\/O bottlenecks for real-time edge data processing.\" class=\"wp-image-2827\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Edge_Database__Analytics-1024x616.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Edge_Database__Analytics-300x180.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Edge_Database__Analytics-768x462.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Edge_Database__Analytics-1536x924.jpg 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/Edge_Database__Analytics.jpg 1540w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Edge Databases<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">Embedded Linux is no longer limited to &#8220;lightweight&#8221; workloads.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udce5 Ready for Evaluation?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Our complete demo system (PetaLinux-based) is available for download and validation on your own hardware.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">\ud83d\udce9 Contact Us<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Interested in breaking your NVMe bottleneck?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\ud83d\udc49 <a href=\"https:\/\/dgway.com\/contact.html\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Contact Our Engineering Team<\/strong><\/a><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">\ud83d\udcc2 Free Evaluation Files<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Download the demo package and test it in your own lab environment:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\ud83d\udc49 <a href=\"https:\/\/dgway.com\/download\/download_form.html?d=rrmNVMeIP_Petalinux_ZCU106_AB17.zip\" target=\"_blank\" rel=\"noreferrer noopener\">rmNVMe-IP on PetaLinux (AMD)<\/a> | <a href=\"https:\/\/dgway.com\/download\/download_form.html?d=rmNVMeIPG4_Config_AGLF3V.zip\" target=\"_blank\" rel=\"noreferrer noopener\">rmNVMe-IP Gen4 (Altera)<\/a><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">\ud83d\udd0e Learn More<\/h3>\n\n\n\n<h3 class=\"wp-block-heading\">Product Page<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">\ud83d\udd17 <a href=\"https:\/\/dgway.com\/rmNVMe-IP_X_E.html\" target=\"_blank\" rel=\"noreferrer noopener\">rmNVMe-IP (AMD)<\/a> | <a href=\"https:\/\/dgway.com\/rmNVMe-IP_A_E.html\" target=\"_blank\" rel=\"noreferrer noopener\">rmNVMe-IP (Altera)<\/a><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Technical Documents<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">\ud83d\udd17 rmNVMe-IP on PetaLinux (AMD): <a href=\"https:\/\/dgway.com\/products\/IP\/NVMe-IP\/rmNVMeIP-PetaLinux-instruction-amd\/\" target=\"_blank\" rel=\"noreferrer noopener\">Instruction<\/a><br>\ud83d\udd17 rmNVMe-IP Gen4 (Altera): <a href=\"https:\/\/dgway.com\/products\/IP\/NVMe-IP\/dg_rmnvme_ip_data_sheet_g4_intel\/\">Datasheet<\/a> | <a href=\"https:\/\/dgway.com\/products\/IP\/NVMe-IP\/dg_rmnvmeip_refdesign_g4_intel\/\">Reference Design<\/a><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">\ud83e\udd1d Official Partner Platforms<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Available via:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.amd.com\/en\/search\/partner\/embedded-partner-solutions.html\/7554\" target=\"_blank\" rel=\"noreferrer noopener\">AMD Adaptive Computing Partner<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.altera.com\/asap\/offering\/po-1885\/random-access-multi-user-nvme-gen5-ip-core-rmnvme-ip?q=1735685858\" target=\"_blank\" rel=\"noreferrer noopener\">Altera Solution Acceleration Partner<\/a><\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udd25 Final Takeaway<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Achieving <strong>6,300 MB\/s file-system performance on Embedded Linux<\/strong> is not about one trick.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It requires:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u2714 Gen4-ready SSD interface <br>\u2714 Full hardware NVMe offload <br>\u2714 High-speed dual-channel DMA <br>\u2714 Application-level optimization with io_uring<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">When every layer is optimized \u2014 embedded platforms can deliver data-center-class storage performance.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\">If your edge system is still capped at 1.6 GB\/s, it\u2019s time to redesign the architecture.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Let\u2019s unlock Gen4 performance together \ud83d\ude80<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/dgway.com\/contact.html\" target=\"_blank\" rel=\" noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"341\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/PetaLinux_rmNVMeG4_Footer-1024x341.jpg\" alt=\"Highlighting 6,300 MB\/s NVMe file system performance on MPSoC platforms, featuring Gen4 NVMe acceleration, high-speed SSD storage, and a call-to-action for data storage and data center applications seeking to eliminate I\/O bottlenecks.\" class=\"wp-image-2831\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/PetaLinux_rmNVMeG4_Footer-1024x341.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/PetaLinux_rmNVMeG4_Footer-300x100.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/PetaLinux_rmNVMeG4_Footer-768x256.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/02\/PetaLinux_rmNVMeG4_Footer.jpg 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In traditional FPGA-based Embedded Linux systems, NVMe storage performance typically stalls at ~1,600 MB\/s. Why? Because most MPSoCs rely on: The result? A serious performance bottleneck that prevents modern Gen4 SSDs from reaching their true potential. But what if embedded platforms could break that limit? Today, we demonstrate 6,300 MB\/s sustained file system write performance on a Linux-based AMD Zynq&#46;&#46;&#46;<\/p>\n","protected":false},"author":1,"featured_media":2822,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[992,982,127,271,981,990,40,238,997,303,984,523,991,987,994,988,995,985,251,986,989,275,993,861,812,856,996,983,436],"class_list":["post-2816","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-storage","tag-axi-dma","tag-data-center-storage","tag-design-gateway","tag-edge-computing","tag-embedded-linux","tag-ext4-performance","tag-fpga","tag-hardware-acceleration","tag-hardware-nvme-driver","tag-high-performance-computing-2","tag-high-throughput-storage","tag-high-speed-data-logging","tag-industrial-data-acquisition","tag-io_uring-performance","tag-linux-kernel-driver","tag-linux-nvme-optimization","tag-low-latency-storage-2","tag-mpsoc-storage-performance","tag-nvme","tag-nvme-gen4-on-fpga","tag-nvme-hardware-offload","tag-nvme-ip-core","tag-pcie-architecture","tag-pcie-gen4","tag-pcie-soft-ip","tag-petalinux","tag-ssd-benchmark","tag-storage-performance","tag-zynq-ultrascale"],"_links":{"self":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts\/2816","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/comments?post=2816"}],"version-history":[{"count":3,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts\/2816\/revisions"}],"predecessor-version":[{"id":2833,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts\/2816\/revisions\/2833"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/media\/2822"}],"wp:attachment":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/media?parent=2816"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/categories?post=2816"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/tags?post=2816"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}