YAMAMOTO Takashi 6e3c3fe9ec Fix build error with LLVM 16 (#2259) пре 2 година
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basic 37b09d0f24 Expose wasm_runtime_call_indirect (#1969) пре 2 година
file 09a2698bba Remove a file test outside of the specs and improve CI reporting (#2057) пре 2 година
gui 4cd88a96d5 Add more types and APIs for attr_container (#1841) пре 3 година
littlevgl 9cf7b88bad Enhance cmake makefiles (#1390) пре 3 година
multi-module 654ac5feca Use cmake POSITION_INDEPENDENT_CODE instead of hardcoding -pie -fPIE (#1598) пре 3 година
multi-thread 216dc43ab4 Use shared memory lock for threads generated from same module (#1960) пре 2 година
native-lib 825544ddab samples/native-lib: use the same shared lib name as product-mini (#1669) пре 3 година
ref-types f10563dfb4 Fix typo in samples/ref-types (#2236) пре 2 година
sgx-ra 9b9ae0cfac Update cmake files and wamr-test-suites to support collect code coverage (#1992) пре 2 година
simple 289fc5efbf Enhance/Fix sample socket-api and workload (#2006) пре 2 година
socket-api 289fc5efbf Enhance/Fix sample socket-api and workload (#2006) пре 2 година
spawn-thread 654ac5feca Use cmake POSITION_INDEPENDENT_CODE instead of hardcoding -pie -fPIE (#1598) пре 3 година
wasi-threads 0f73ce1076 Update wasi-libc version in CI and implement custom sync primitives (#2028) пре 2 година
wasm-c-api 6e3c3fe9ec Fix build error with LLVM 16 (#2259) пре 2 година
wasm-c-api-imports 289fc5efbf Enhance/Fix sample socket-api and workload (#2006) пре 2 година
workload 24a7e5c1e6 Update sample workload tensorflow (#2101) пре 2 година
README.md 7701b379e4 Update documents (#2100) пре 2 година

README.md

Samples

  • basic: Demonstrating how to use runtime exposed API's to call WASM functions, how to register native functions and call them, and how to call WASM function from native function.
  • simple: The runtime is integrated with most of the WAMR APP libraries, and a few WASM applications are provided for testing the WAMR APP API set. It uses built-in libc and executes apps in interpreter mode by default.
  • file: Demonstrating the supported file interaction API of WASI. This sample can also demonstrate the SGX IPFS (Intel Protected File System), enabling an enclave to seal and unseal data at rest.
  • littlevgl: Demonstrating the graphic user interface application usage on WAMR. The whole LVGL 2D user graphic library and the UI application are built into WASM application. It uses WASI libc and executes apps in AOT mode by default.
  • gui: Move the LVGL library into the runtime and define a WASM application interface by wrapping the littlevgl API. It uses WASI libc and executes apps in interpreter mode by default.
  • multi-thread: Demonstrating how to run wasm application which creates multiple threads to execute wasm functions concurrently, and uses mutex/cond by calling pthread related API's.
  • spawn-thread: Demonstrating how to execute wasm functions of the same wasm application concurrently, in threads created by host embedder or runtime, but not the wasm application itself.
  • wasi-threads: Demonstrating how to run wasm application which creates multiple threads to execute wasm functions concurrently based on lib wasi-threads.
  • multi-module: Demonstrating the multiple modules as dependencies feature which implements the load-time dynamic linking.
  • ref-types: Demonstrating how to call wasm functions with argument of externref type introduced by reference types proposal.
  • wasm-c-api: Demonstrating how to run some samples from wasm-c-api proposal and showing the supported API's.
  • socket-api: Demonstrating how to run wasm tcp server and tcp client applications, and how they communicate with each other.
  • native-lib: Demonstrating how to write required interfaces in native library, build it into a shared library and register the shared library to iwasm.
  • sgx-ra: Demonstrating how to execute Remote Attestation on SGX with librats, which enables mutual attestation with other runtimes or other entities that support librats to ensure that each is running within the TEE.
  • workload: Demonstrating how to build and run some complex workloads, e.g. tensorflow-lite, XNNPACK, wasm-av1, meshoptimizer and bwa.