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Ziye Yang's Projects

cc-trusted-api icon cc-trusted-api

Unified API to Access TCG Compliant measurement, event log, quote in Confidential Computing Environment.

ceph icon ceph

Ceph is a distributed object, block, and file storage platform

cloud-hypervisor icon cloud-hypervisor

A Virtual Machine Monitor for modern Cloud workloads. Features include CPU, memory and device hotplug, support for running Windows and Linux guests, device offload with vhost-user and a minimal compact footprint. Written in Rust with a strong focus on security.

fio icon fio

Flexible I/O Tester

gramine icon gramine

A library OS for Linux multi-process applications, with Intel SGX support

image-service icon image-service

Nydus - the Dragonfly image service, providing fast, secure and easy access to container images.

kata-containers icon kata-containers

Kata Containers version 2.x repository. Kata Containers is an open source project and community working to build a standard implementation of lightweight Virtual Machines (VMs) that feel and perform like containers, but provide the workload isolation and security advantages of VMs. https://katacontainers.io/

kubernetes icon kubernetes

Production-Grade Container Scheduling and Management

nccl icon nccl

Optimized primitives for collective multi-GPU communication

pmdk icon pmdk

Persistent Memory Development Kit

riscv-ap-tee icon riscv-ap-tee

This repo holds the work area and revisions of the RISC-V AP-TEEI specification. This specification defines the programming interfaces (ABI) to support a scalable confidential compute architecture for RISC-V application-processor platforms. The RISC-V AP-TEE Interface is used by OS/VMMs to enable scalable hosting of confidential virtual machines, applications and other workloads where the hosting software, infrastructure, developers and operators are considered outside the Trusted Computing Base (TCB).

spdk icon spdk

Storage Performance Development Kit

veturboio icon veturboio

A library developed by Volcano Engine for high-performance reading and writing of PyTorch model files.

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