Doctoral Thesis Oral Defense - Hugo Sadok

August 27, 2026  9:30AM—11:30AM

Location:
4405 & Zoom - Gates and Hillman Centers

Speaker:
HUGO SADOK, Ph.D. Candidate, Computer Science Department, Carnegie Mellon University
https://hsadok.com/

Generalizing Device Interfaces

Accelerators and I/O devices perform much of today's computation. Accelerators are now commonplace, and even long-established I/O devices such as network cards (NICs) and disks have gained their own compute. Yet devices today communicate using specialized interfaces better suited to an era when each device performed a single, fixed function under the CPU's control. Specialized interfaces limit devices in two ways. First, interfaces are specialized to a particular data format, unable to adapt to new capabilities as devices gain them. Second, interfaces are specialized to a particular pair of endpoints: the device and the CPU. As a result, devices that would benefit from interacting directly must rely on vendor-specific solutions.

A general-purpose interface could address both limits. What stands in the way is the long-held assumption that generality costs performance. This dissertation disproves that assumption, showing that devices can adopt a general-purpose interface without compromising performance—in fact, generality can even improve performance by reducing the CPU's involvement in communication. We pursue generality along two axes: "what" devices communicate and with "whom."

To generalize "what" devices communicate, we introduce Ensō, a streaming abstraction between devices and the CPU. Instead of specializing to the data's format and size, Ensō delivers arbitrary data over a stream. This allows devices to extend their capabilities without shoehorning data into legacy formats. Streaming makes the interface format-agnostic and eliminates the overheads of fixed-size buffers, letting applications achieve up to 6× the throughput of a specialized NIC.

To generalize with "whom" devices can communicate, we introduce DCP, a general-purpose peer-to-peer Device Communication Protocol. Although interconnects such as PCIe support peer-to-peer communication, device interfaces are asymmetric, designed for talking to the CPU. DCP instead provides a symmetric interface that works the same way regardless of devices' capabilities, without relying on the CPU for coordination. As a result, DCP cuts latency by 83% compared to CPU-mediated communication.

Together, Ensō and DCP show that devices need not remain workers behind restricted interfaces, but can instead act as peers—enabling a future in which a computer looks less like a hub-and-spoke and more like a distributed system of composable accelerators.

Thesis Committee:

Justine Sherry (Chair)
David G. Andersen
James C. Hoe
Arvind Krishnamurthy (University of Washington)
Aurojit Panda (New York University)

In-person and Zoom

Contact
Matt Stewart


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