Enhancing dma-buf Subsystem: Toward Efficient User-Space Read/Write Operations

Introduction

The Linux kernel's dma-buf subsystem has long been a cornerstone for efficient memory buffer sharing between drivers, particularly for device-to-device I/O. At the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF), a joint session led by Pavel Begunkov, with assistance from Kanchan Joshi, delved into proposals to make dma-buf usage more efficient and, crucially, to enable read and write operations directly from user space. This article explores the dma-buf subsystem, its current limitations, and the path toward a more versatile I/O interface.

What is dma-buf?

The dma-buf framework provides a standardized way for kernel drivers to share memory buffers that are mapped for Direct Memory Access (DMA). It abstracts the underlying memory allocation and synchronization, allowing multiple drivers (e.g., a GPU and a network card) to exchange data without copying. This zero-copy approach is essential for high-throughput applications like video streaming, machine learning inference, and storage offload.

Traditionally, dma-buf focused on exporter-importer relationships: a driver that creates the buffer (exporter) passes a file descriptor to another driver (importer), which then maps the buffer into its own I/O address space. User-space processes could only interact with dma-bufs indirectly, via ioctl() calls or by attaching the buffer to a graphics context—there was no native mechanism for reading from or writing to a dma-buf using standard file I/O operations like read() or write().

Current Limitations

The absence of direct read/write support creates several inefficiencies:

• Complexity for user-space applications: To transfer data into or out of a dma-buf, developers must either copy data to a temporary buffer or use vendor-specific APIs, defeating the zero-copy advantage.
• Lack of integration with existing I/O frameworks: Modern Linux I/O mechanisms like io_uring and AIO cannot directly operate on dma-bufs, limiting their applicability in storage and networking stacks.
• Performance bottlenecks: When user space needs to inject data into a device pipeline (e.g., for FPGA accelerators), the extra copy or mapping overhead can reduce overall throughput.

The Need for Read/Write Operations

Enabling read() and write() on dma-buf file descriptors would allow user-space applications to treat dma-bufs as regular files, leveraging the kernel's page cache, buffer management, and asynchronous I/O subsystems. This would unlock several use cases:

• Storage offload: Directly write storage data into GPU memory for compute tasks, bypassing intermediate copies.
• Network packet processing: Read packets from a dma-buf shared with a smartNIC without copying to user-space buffers.
• Machine learning pipelines: Stream training data from storage into accelerator memory through a familiar, standard I/O path.

The 2026 LSFMM+BPF Summit Discussion

At the summit, Pavel Begunkov and Kanchan Joshi presented a proposal to add a read/write I/O path to the dma-buf subsystem. Key points included:

• Buffered vs. direct I/O: The design must handle both cached (buffered) and uncached (direct) access, similar to regular files. For dma-bufs, direct I/O would be more common to maintain zero-copy semantics.
• Synchronization: Reading from a dma-buf that is being written by a device requires careful fencing. The proposal leverages existing dma-buf fence mechanisms to ensure data consistency.
• Integration with io_uring: By supporting IORING_OP_READ and IORING_OP_WRITE on dma-buf fds, applications could submit asynchronous I/O operations without context switches, a major performance win.
• Memory mapping considerations: The new operations would coexist with existing mmap() support, allowing user space to choose between memory-mapped access and streaming I/O as appropriate.

Proposed Solutions and Benefits

The summit attendees discussed several technical approaches:

1. Extending the dma-buf file operations: Implement the read_iter and write_iter file_operations in the dma-buf core, with a fallback to a generic copy that respects the buffer's caching attributes.
2. Using scatter-gather lists: For multiple disjoint memory regions within a dma-buf, the I/O path would operate on scatterlists to maintain efficient DMA mappings.
3. Fence integration: Any read/write operation would automatically attach a fence that completes only after the buffer is no longer in use by hardware, avoiding stale data consumption.

Benefits include:

• Simplified application code: Developers can use standard Linux I/O APIs (read/write/pread/pwrite) without needing specialized libraries.
• Better resource utilization: Zero-copy transfers reduce CPU load and memory bandwidth usage, critical for data-center workloads.
• Future-proofing: Aligning dma-buf with the kernel's evolving I/O stack (e.g., io_uring) ensures compatibility with emerging high-performance storage devices.

Future Directions

While the session was largely exploratory, it set the stage for concrete patches. Challenges remain, such as handling cache coherency on architectures with non-coherent DMA, and defining the exact semantics when multiple readers/writers share a buffer. The community is expected to continue the discussion on the linux-mm and linux-fsdevel mailing lists.

As the dma-buf subsystem evolves, it will likely become a key enabler for heterogeneous computing and disaggregated hardware, where user-space processes frequently need to move data among accelerators, storage, and networking devices with minimal overhead.

Conclusion

The proposal to add read and write support to dma-bufs, as debated at LSFMM+BPF 2026, represents a natural progression of Linux's memory management and I/O capabilities. By allowing user-space to read from and write to shared DMA buffers using standard file operations, the kernel can simplify programming models, reduce data copies, and improve performance in a wide range of modern workloads. With leaders like Pavel Begunkov and Kanchan Joshi driving the effort, the Linux community is poised to deliver another powerful tool for high-performance computing.