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<a href="https://github.com/ParCoreLab/UniConn" class="text-xl font-semibold font-serif visited:text-teal-700">Unified Communication Library</a>
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<a href="https://github.com/ParCoreLab/" class="text-xl font-semibold font-serif visited:text-teal-700">Unified Communication Library</a>
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<p class="text-lg">We're undertaking the design of an API for a unified communication library to streamline device-to-device communication within the CPU-free model by aiming to optimize communication efficiency across diverse devices. More details about the project will be available soon. The related paper is under preparation.</p>
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<p class="text-lg">We're undertaking the design of an API for a unified communication library to streamline device-to-device communication within the CPU-free model by aiming to optimize communication efficiency across diverse devices. We are also investigating how the available communication libraries for a system perform under different
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message sizes and communication patterns. Thus, we ex-
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tensively benchmark current communication methods for
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single-process, multi-threaded, and multi-process codes. More details about the project will be available soon. The related paper is under preparation.</p>
<a href="https://github.com/ParCoreLab/CPU-Free-Model-Compiler" class="text-xl font-semibold font-serif visited:text-teal-700">CPU Free Model Compiler</a>
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<a href="https://github.com/ParCoreLab/" class="text-xl font-semibold font-serif visited:text-teal-700">CPU Free Model Compiler</a>
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<p class="text-lg">We're actively crafting a compiler to empower developers to write high-level Python code that compiles into efficient CPU-free device code. This compiler integrates GPU-initiated communication libraries, NVSHMEM for NVIDIA and ROC_SHMEM for AMD, enabling GPU communication directly within Python code. With automatic generation of GPU-initiated communication calls and persistent kernels, we aim to streamline development workflows. Our prototype will be available soon.</p>
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