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llvm-project
llvm-project PublicForked from llvm/llvm-project
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
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AdaptiveCpp
AdaptiveCpp PublicForked from AdaptiveCpp/AdaptiveCpp
Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications …
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yambo
yambo PublicForked from yambo-code/yambo
This is the official GPL repository of the yambo code
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carm-roofline
carm-roofline PublicForked from champ-hub/carm-roofline
Cross-platform Cache-Aware Roofline Model (CARM) and Application Benchmarking Tool for Intel, AMD, ARM, and RISC-V CPUs
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Repositories
- llvm-project Public Forked from llvm/llvm-project
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
SiPearl/llvm-project’s past year of commit activity - vllm Public Forked from vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
SiPearl/vllm’s past year of commit activity - xgboost Public Forked from dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
SiPearl/xgboost’s past year of commit activity - AdaptiveCpp Public Forked from AdaptiveCpp/AdaptiveCpp
Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
SiPearl/AdaptiveCpp’s past year of commit activity - kokkos Public Forked from kokkos/kokkos
Kokkos C++ Performance Portability Programming Ecosystem: The Programming Model - Parallel Execution and Memory Abstraction
SiPearl/kokkos’s past year of commit activity - model-collection Public Forked from AI4SIM/model-collection
This project contains a collection of deep learning models developed by the AI4Sim team with various partners. This is structured on the basis of use-cases providing canonical PyTorch Lightning pipelines allowing to train neural network models that are able to surrogate various physical processes.
SiPearl/model-collection’s past year of commit activity
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