mit-han-lab / inter-operator-schedulerLinks
[MLSys 2021] IOS: Inter-Operator Scheduler for CNN Acceleration
☆200Updated 3 years ago
Alternatives and similar repositories for inter-operator-scheduler
Users that are interested in inter-operator-scheduler are comparing it to the libraries listed below
Sorting:
- Automatic Schedule Exploration and Optimization Framework for Tensor Computations☆177Updated 3 years ago
- PET: Optimizing Tensor Programs with Partially Equivalent Transformations and Automated Corrections☆121Updated 3 years ago
- Benchmark scripts for TVM☆74Updated 3 years ago
- DietCode Code Release☆64Updated 2 years ago
- System for automated integration of deep learning backends.☆47Updated 2 years ago
- play gemm with tvm☆91Updated last year
- ☆195Updated 2 years ago
- A home for the final text of all TVM RFCs.☆105Updated 9 months ago
- ☆145Updated 5 months ago
- ☆92Updated 2 years ago
- tophub autotvm log collections☆69Updated 2 years ago
- Fast CUDA Kernels for ResNet Inference.☆176Updated 6 years ago
- Dynamic Tensor Rematerialization prototype (modified PyTorch) and simulator. Paper: https://arxiv.org/abs/2006.09616☆132Updated 2 years ago
- SparseTIR: Sparse Tensor Compiler for Deep Learning☆138Updated 2 years ago
- ☆40Updated 3 years ago
- Automatic Mapping Generation, Verification, and Exploration for ISA-based Spatial Accelerators☆113Updated 2 years ago
- An extention of TVMScript to write simple and high performance GPU kernels with tensorcore.☆50Updated 11 months ago
- An unofficial cuda assembler, for all generations of SASS, hopefully :)☆83Updated 2 years ago
- ☆99Updated 3 months ago
- ☆69Updated 2 years ago
- heterogeneity-aware-lowering-and-optimization☆255Updated last year
- ☆36Updated 2 years ago
- Repository for SysML19 Artifacts Evaluation☆54Updated 6 years ago
- examples for tvm schedule API☆101Updated 2 years ago
- ☆149Updated 11 months ago
- ☆39Updated 5 years ago
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆92Updated last week
- The quantitative performance comparison among DL compilers on CNN models.☆74Updated 4 years ago
- ☆236Updated 2 years ago
- ☆43Updated last year