In an interesting development for the GPU industry, PCIe-attached memory is set to change how we think about GPU memory capacity and performance. Panmnesia, a company backed by South Korea’s KAIST research institute, is working on a technology called Compute Express Link, or CXL, that allows GPUs to utilize external memory resources via the PCIe interface.
Traditionally, GPUs like the RTX 4060 are limited by their onboard VRAM, which can bottleneck performance in memory-intensive tasks such as AI training, data analytics, and high-resolution gaming. CXL leverages the high-speed PCIe connection to attach external memory modules directly to the GPU.
This method provides a low-latency memory expansion option, with performance metrics showing significant improvements over traditional methods. According to reports, the new technology manages to achieve double-digit nanosecond latency, which is a substantial reduction compared to standard SSD-based solutions.
Moreover, this technology isn’t limited to just traditional RAM. SSDs can also be used to expand GPU memory, offering a versatile and scalable solution. This capability allows for the creation of hybrid memory systems that combine the speed of RAM with the capacity of SSDs, further enhancing performance and efficiency.
While CXL operates on a PCIe link, integrating this technology with GPUs isn’t straightforward. GPUs lack the necessary CXL logic fabric and subsystems to support DRAM or SSD endpoints. Therefore, simply adding a CXL controller is not feasible.
GPU cache and memory systems only recognize expansions through Unified Virtual Memory (UVM). However, tests done by Panmnesia revealed that UVM had the poorest performance among tested GPU kernels due to overhead from host runtime intervention during page faults and inefficient data transfers at the page level.
To address the issue, Panmnesia developed a series of hardware layers that support all key CXL protocols, consolidated into a unified controller. This CXL 3.1-compliant root complex includes multiple root ports for external memory over PCIe and a host bridge with a host-managed device memory decoder. This decoder connects to the GPU’s system bus and manages the system memory, providing direct access to expanded storage via load/store instructions, effectively eliminating UVM’s issues.
The implications of this technology are far-reaching. For AI and machine learning, the ability to add more memory means handling larger datasets more efficiently, accelerating training times, and improving model accuracy. In gaming, developers can push the boundaries of graphical fidelity and complexity without being constrained by VRAM limitations.
For data centers and cloud computing environments, Panmnesia’s CXL technology provides a cost-effective way to upgrade existing infrastructure. By attaching additional memory through PCIe, data centers can enhance their computational power without requiring extensive hardware overhauls.
Despite its potential, Panmnesia faces a big challenge in gaining industrywide adoption. The best graphics cards from AMD and Nvidia don’t support CLX, and they may never support it. There’s also a high possibility that industry players might develop their own PCIe-attached memory technologies for GPUs. Nonetheless, Panmnesia’s innovation represents a step forward in addressing GPU memory bottlenecks, with the potential to impact high-performance computing and gaming significantly.
Nearly a month after announcing the GPT-6.1 Sol model, OpenAI unveiled GPT-6.1 Terra today. The latest addition to the family focuses on computer use, visual reasoning, coding, and professional work, while costing 50% less through the API than GPT-5.6 Terra.
OpenAI says Terra can handle everything from filling out browser forms and working inside spreadsheets to interpreting technical drawings and editing videos. The company says it can also complete computer-based tasks more than three times faster than GPT-6 Astra and GPT-6.1 Sol.
ASUS has started selling its UGen Intel Arc Pro B70 graphics card in Europe, bringing its take on Intel’s workstation GPU to customers with a hefty €1,799 recommended price. The card is available in Germany and Austria, while ASUS lists it at CHF 1,799 in Switzerland.
Intel first introduced the Arc Pro B70 in March 2026, with its own branded model starting at $949. ASUS’s version arrives several months later with the same core GPU architecture but a different cooling design and a higher power rating. The price also places it well above Intel’s original starting point, although the two prices are not directly comparable because ASUS’s European figure includes VAT.
Anthropic has officially filed to go public, and buried inside its S-1 is a blunt warning about the technology at the center of its business. The maker of Claude AI says advanced AI could cause everything from large-scale cyberattacks and geopolitical instability to catastrophic or even existential risks for humanity.
The warnings take up a surprisingly large part of the filing. Axios notes that more than 90 pages, or roughly a third of the prospectus, focus on risk factors. Many of them warn about what could happen as AI systems become more capable and autonomous.