llm-d/llm-d
Feb 2026 – Jul 2026
4 Months active
Languages Used
DockerfileYAMLMarkdown
Technical Skills
CI/CDContainerizationDevOpsMachine LearningCloud InfrastructureGPU Computing
Vincent Cavé
PROFILE
Vincent Cavé
Worked on the llm-d/llm-d repository to deliver four major features focused on enabling and optimizing AMD GPU support for machine learning inference. Over four months, implemented ROCm-compatible Dockerfiles, upgraded container images, and refined YAML-based deployment configurations to support models like Qwen3-32B and vLLM. Leveraged skills in containerization, DevOps, and GPU computing to enhance deployment reliability, resource utilization, and cross-hardware compatibility. Collaborated with teams from AMD, IBM, and Red Hat to validate changes and improve documentation. Used Dockerfile, YAML, and Python to modernize the ROCm ecosystem, streamline CI/CD workflows, and lay the groundwork for scalable, cost-effective deployments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
4
Lines of code
1,169
Activity Months4
Your Network
1788 peopleSame Organization
@amd.com1657
7b30f3f5e26d48061f873d04cc7e1d1f_amdengMember
GunaShekar, AjayMember
aasbodduMember
Abdul Lateef AttarMember
Acim MaravicMember
Adam DickinMember
Pryor, AdamMember
Pryor, AdamMember
Adel JoharMember
Work History
July 2026
1 Commits • 1 Features
Jul 1, 2026July 2026 monthly summary for llm-d/llm-d focused on upgrading ROCm tooling and Docker image to align with the latest ROCm ecosystem. Delivered updated dependencies (vLLM 0.23.0, NIXL-ROCm, MORI v1.2.0) to improve compatibility, reliability, and potential performance benefits for ROCm workflows. The work is aligned with ongoing platform modernization and supports broader deployment scenarios.
1 Commits • 1 Features
Jul 1, 2026July 2026 monthly summary for llm-d/llm-d focused on upgrading ROCm tooling and Docker image to align with the latest ROCm ecosystem. Delivered updated dependencies (vLLM 0.23.0, NIXL-ROCm, MORI v1.2.0) to improve compatibility, reliability, and potential performance benefits for ROCm workflows. The work is aligned with ongoing platform modernization and supports broader deployment scenarios.
July 2026
May 2026
1 Commits • 1 Features
May 1, 2026May 2026 monthly summary for llm-d/llm-d: Delivered ROCm Docker Image Enhancement for AMD/vLLM Baseline Support. Upgraded ROCm Dockerfile to vllm v0.20.1, updated RIXL to 39be1de, optimized CPU resources for AMD/vLLM, and added AMD/SGLang optimized-baseline support. This work aligns with AMD-friendly baseline goals, enabling faster inference and easier maintenance on AMD hardware. No major bugs fixed this month; primary focus was feature delivery and baseline alignment. Technologies demonstrated include ROCm, vLLM, Docker, and AMD/SGLang baseline integration.
May 2026
1 Commits • 1 Features
May 1, 2026May 2026 monthly summary for llm-d/llm-d: Delivered ROCm Docker Image Enhancement for AMD/vLLM Baseline Support. Upgraded ROCm Dockerfile to vllm v0.20.1, updated RIXL to 39be1de, optimized CPU resources for AMD/vLLM, and added AMD/SGLang optimized-baseline support. This work aligns with AMD-friendly baseline goals, enabling faster inference and easier maintenance on AMD hardware. No major bugs fixed this month; primary focus was feature delivery and baseline alignment. Technologies demonstrated include ROCm, vLLM, Docker, and AMD/SGLang baseline integration.
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly performance-focused summary for llm-d/llm-d. This period centered on delivering a high-impact model inference optimization through AMD-prefill and decode disaggregation, coupled with targeted code quality improvements and cross-team collaboration to enable broader hardware support and scalable inference.
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly performance-focused summary for llm-d/llm-d. This period centered on delivering a high-impact model inference optimization through AMD-prefill and decode disaggregation, coupled with targeted code quality improvements and cross-team collaboration to enable broader hardware support and scalable inference.
March 2026
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary: Delivered AMD Inference Scheduling and ROCm Docker Compatibility to enable deployment on AMD GPUs. Implemented ROCm-compatible Dockerfile, updated inference scheduling YAML, and CI/build rules to support AMD hardware. Validated deployments using Qwen3-32B with llm-d-rocm images. These changes broaden hardware support, improve deployment reliability, and enhance CI reproducibility, driving lower TCO and greater throughput.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary: Delivered AMD Inference Scheduling and ROCm Docker Compatibility to enable deployment on AMD GPUs. Implemented ROCm-compatible Dockerfile, updated inference scheduling YAML, and CI/build rules to support AMD hardware. Validated deployments using Qwen3-32B with llm-d-rocm images. These changes broaden hardware support, improve deployment reliability, and enhance CI reproducibility, driving lower TCO and greater throughput.
Activity
Loading activity data...
Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage45.0%
Skills & Technologies
Programming Languages
DockerfileMarkdownYAML
Technical Skills
AMD ROCmCI/CDCloud InfrastructureContainerizationDevOpsDockerGPU ComputingKubernetesMachine LearningPython
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline