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  • pdf文档 Dynamic Model in TVM

    reserved. Relay virtual machine Relay Executable relay.vm.compile Relay Object (hardware independent) Code segment VM Func 0 VM Func 1 ... VM Func N Data segment Const 0 Const 1 ... Const K Func 0 Packed Func 1 ... Packed Func M Relay VM Executor exe = relay.vm.compile(mod, target) vm = relay.vm.VirtualMachine(exe) vm.init(ctx) vm.invoke("main", *args) export© 2019, Amazon Web Services Services, Inc. or its Affiliates. All rights reserved. VM bytecode Instruction Description Move Moves data from one register to another. Ret Returns the object in register result to caller’s register
    0 码力 | 24 页 | 417.46 KB | 5 月前
    3
  • pdf文档 OctoML OSS 2019 11 8

    forimproved multi-language support for expPosing runtime, and |IRs. QQ octoML Unified Object Protocol vm::Object NDArray | Rd | tuplelclosure AST Nodes Cross language suppPort Easy to introduce new and OctoML. e Initial implementation is quickly moving towards production quality. o _VM compiler VM runtime VM serialization Dynamic Shape Support Dynamic Shape Allocation o Dynamic Shape Code generation this part of the systeml e Haichen and | will discuss more details at TVMConf. Oo oo QQ octoML 11 VM Memory Planning e Recently shipped a first version fn enain(0) -> Tensor[tk,),f32] { ofdynamicmemory
    0 码力 | 16 页 | 1.77 MB | 5 月前
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  • pdf文档 Bring Your Own Codegen to TVM

    external codegen mod = relay.build_extern(mod, “dnnl”) 4. Run the inference exe = relay.create_executor(“vm”, mod=mod, ctx=tvm.cpu(0)) data = np.random.uniform(size=(1, 3, 224, 224)).astype(“float32”) out = Partitioning Your Codegen LLVM, CUDA, Metal, VTA Serialized Subgraph Library Relay Runtime (VM, Graph Runtime, Interpreter) Your Dispatcher Target Device General Devices (CPU/GPU/FPGA) Mark Partitioning Your Codegen LLVM, CUDA, Metal, VTA Serialized Subgraph Library Relay Runtime (VM, Graph Runtime, Interpreter) Your Dispatcher Target Device General Devices (CPU/GPU/FPGA) Mark
    0 码力 | 19 页 | 504.69 KB | 5 月前
    3
  • pdf文档 Trends Artificial Intelligence

    in 2020. Cloud & data center capex includes Google, Amazon, Microsoft, Meta, Alibaba, Apple, IBM, Oracle, Tencent, & Baidu for ten years ending 2022. ‘Tens of billions of units’ refers to the potential operators) are Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), Alibaba Cloud, Oracle Cloud Infrastructure (OCI), IBM Cloud & Tencent Cloud. AI User + Usage + CapEx Growth = Unprecedented96 revenue” on like-for-like basis so data represents best estimates and may not align between companies. Oracle Cloud revenue includes Cloud Services & License Support, as well as Cloud License & On-Premise License
    0 码力 | 340 页 | 12.14 MB | 4 月前
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