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[TRTLLM-17005][refactor] Component-local C++ Tests (Part 5) - #21024
The change extracts profiler, runtime, executor, batch-manager, PEFT-cache, and user-buffer code into component libraries. It replaces broad shared-library dependencies with explicit links and updates unit-test registrations with component owners, dependencies, and scheduling labels.
Review risks include incomplete CMake dependencies, symbol retention, and configuration differences across CUDA, NCCL, NVSHMEM, Python, and NIXL builds. The explicit user-buffer source list also needs maintenance when sources change. No current review findings were supplied, so review finding counts are unavailable.
QA Engineer Review
The change updates C++ unit-test registrations under cpp/tests/unit_tests/ and changes genUniqueAgentNameTest.cpp to include agentName.h. The registrations cover context-transfer vote reduction, PEFT caching, profiler utilities, serialization, agent-name generation, user buffers, runtime memory and utility components, and Torch utilities. The supplied evidence does not identify changes to test functions or IDs; the existing tests cover these behaviors.
No matching entries for these C++ tests were found in the searched tests/integration/test_lists/ paths. Test execution results and coverage sufficiency are not established. The supplied CI notes report mixed outcomes and a multi-GPU approval-label requirement. Coverage verdict: needs follow-up.
Per-File QA Perspective
cpp/tensorrt_llm/CMakeLists.txt: Whole-archive and link-library component sets change. Verify symbol retention and linkage in supported builds.
cpp/tensorrt_llm/batch_manager/CMakeLists.txt: Adds libraries for PEFT caching, context-transfer consensus, and request information. Verify dependencies and downstream linkage.
cpp/tensorrt_llm/batch_manager/contextTransferCoordinator.cpp: Removes the vote-reducer implementation. Verify coordinator behavior after the move.
cpp/tensorrt_llm/batch_manager/contextTransferVoteReducer.cpp: Adds vote aggregation, conflict checks, timeout handling, and cleanup. Verify participant validation, duplicate votes, and readiness results.
cpp/tensorrt_llm/batch_manager/dataTransceiver.cpp: Removes RequestInfo implementations. Verify consumers link to the extracted implementation.
cpp/tensorrt_llm/batch_manager/requestInfo.cpp: Adds request metadata accessors and serialization. Verify round trips, field ordering, and equality behavior.
cpp/tensorrt_llm/common/CMakeLists.txt: Extracts profiler utilities into a static library. Verify profiler consumers link without the shared library.
cpp/tensorrt_llm/executor/CMakeLists.txt: Adds memory-descriptor and agent-name libraries. Verify component linkage.
cpp/tensorrt_llm/executor/cache_transmission/agent_utils/agentName.cpp: Adds unique-name generation with host, process ID, random suffix, and counter. Verify uniqueness and thread safety.
cpp/tensorrt_llm/executor/cache_transmission/agent_utils/agentName.h: Declares the name helper in a new header. Verify callers use the correct header and namespace.
cpp/tensorrt_llm/executor/cache_transmission/agent_utils/connection.cpp: Removes moved name-generation and serialization implementations. Verify connection behavior and serialization linkage.
cpp/tensorrt_llm/executor/cache_transmission/agent_utils/connection.h: Moves the name-helper declaration to agentName.h. Verify callers include the new header.
cpp/tensorrt_llm/executor/memoryDesc.cpp: Adds memory-descriptor serialization. Verify field order and serialized-size agreement.
cpp/tensorrt_llm/kernels/userbuffers/CMakeLists.txt: Changes user buffers to a static library with explicit sources and optional NCCL linkage. Verify single- and multi-device builds.
cpp/tensorrt_llm/runtime/CMakeLists.txt: Splits runtime code into component libraries. Verify optional IPC/NVLS dependencies and linkage across build configurations.
cpp/tensorrt_llm/thop/CMakeLists.txt: Decouples Torch utilities from the shared library. Verify Python- and Torch-enabled builds.
cpp/tests/unit_tests/batch_manager/CMakeLists.txt: Registers context-transfer and PEFT-cache tests with component libraries. Verify dependencies and host/GPU scheduling.
cpp/tests/unit_tests/common/CMakeLists.txt: Changes profiler-test ownership and labels. Verify the test’s component linkage and scheduling.
cpp/tests/unit_tests/executor/CMakeLists.txt: Updates serialization and agent-name test dependencies and labels. Verify both tests in their configured environments.
cpp/tests/unit_tests/executor/genUniqueAgentNameTest.cpp: Includes the new agent-name header. Existing tests cover name format, suffix stability, counter increments, uniqueness, and thread safety.
cpp/tests/unit_tests/multi_gpu/CMakeLists.txt: Registers the user-buffer test with focused libraries and multi-GPU labels. Verify scheduling and optional NCCL linkage.
cpp/tests/unit_tests/runtime/CMakeLists.txt: Updates runtime test links and host/GPU labels. Verify GPU requirements and discovery on applicable workers.
cpp/tests/unit_tests/thop/CMakeLists.txt: Registers the Torch utility test through tllm::torch_utils. Verify registration and linkage when BUILD_PYT is enabled.
Description
Refactor C++ build dependencies and test registration so more unit tests can build independently of libtensorrt_llm.so.
Extracts reusable libraries for profiling, worker pools, NumPy I/O, GDRCopy, locality, IPC/NVLS memory, LoRA modules/cache, runtime utilities, and PEFT caching.
Separates smaller executor and batch-manager utilities, including agent-name generation, memory descriptors, request information, and context-transfer vote reduction.
Migrates unit tests to add_tllm_gtest with explicit component dependencies, owners, and scheduling labels. Tests requiring the full library are explicitly marked FULL_STACK.
Decouples Torch utilities from the inference shared library and converts user-buffer kernels into a focused static library with explicit dependencies.
Test Coverage
PR Checklist
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PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
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Reviewing files that changed from the base of the PR and between 59ba526 and 5c9b923.
Files selected for processing: 6
cpp/tests/unit_tests/batch_manager/CMakeLists.txt
cpp/tests/unit_tests/common/CMakeLists.txt
cpp/tests/unit_tests/executor/CMakeLists.txt
cpp/tests/unit_tests/multi_gpu/CMakeLists.txt
cpp/tests/unit_tests/runtime/CMakeLists.txt
cpp/tests/unit_tests/thop/CMakeLists.txt
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Walkthrough
The C++ build now compiles common, runtime, batch-manager, executor, and user-buffer components as separate static libraries. Top-level linking and unit-test registrations use the new targets.
Changes
C++ Componentization
Layer / File(s)
Summary
Runtime, common, and user-buffer targets cpp/tensorrt_llm/common/CMakeLists.txt, cpp/tensorrt_llm/runtime/CMakeLists.txt, cpp/tensorrt_llm/kernels/userbuffers/CMakeLists.txt
Adds static targets and aliases for common profiling, runtime components, and user buffers. User buffers use an explicit source list and target-specific dependencies and properties.
Builds the vote reducer, request information, and PEFT cache as separate libraries. The vote reducer tracks participant votes and timeouts. RequestInfo implements field access and serialization in a separate source file.
Adds separate targets for agent-name generation and memory descriptors. Agent names combine hostname, process ID, a process-wide random suffix, and an incrementing counter. Memory descriptor serialization handles the address, length, and device ID.
Link integration cpp/tensorrt_llm/CMakeLists.txt, cpp/tensorrt_llm/thop/CMakeLists.txt
Expands whole-archive linking and link-library overrides for component targets. The Torch utility target adds a tllm::runtime_buffers dependency and a namespaced alias.
The inspected test scheduling remains GPU-backed, and the copyright header is compliant. No actionable merge-blocking risk remains from these concerns.
Pre-merge checks: 4 · 1
Failed checks: 1 warning
Check name
Status
Explanation
Resolution
Docstring Coverage
Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within survi…
Write docstrings for the functions missing them to satisfy the coverage threshold.
Passed checks: 4 passed
Check name
Status
Explanation
Title check
The title follows the required [TICKET][type] Summary format and names a real part of the change: refactoring C++ build dependencies and test registration so unit tests can build independently. It is …
Description check
The description covers the main content. It has a Description section that lists the extracted libraries, the separated executor and batch-manager utilities, the test migration to add_tllm_gtest with …
Linked Issues check
Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check
Check skipped because no linked issues were found for this pull request.
Full details: Title check
Explanation
The title follows the required [TICKET][type] Summary format and names a real part of the change: refactoring C++ build dependencies and test registration so unit tests can build independently. It is partially related because the changeset also covers executor and batch-manager utilities, Torch decoupling, and user-buffer kernels, which the title does not name. The ticket tag [TRTLLM-17005] and the [refactor] type are present.
Full details: Description check
Explanation
The description covers the main content. It has a Description section that lists the extracted libraries, the separated executor and batch-manager utilities, the test migration to add_tllm_gtest with owners and labels, and the Torch and user-buffer changes. The PR Checklist is marked as reviewed. The Test Coverage section is still the empty template placeholder, with no tests listed. The description also omits the template's short issue-and-solution framing, and it keeps the template HTML comment block.
Full details: Docstring Coverage
Explanation
Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within surviving functions are included; unchanged diff context and fully deleted functions are excluded. Analyzed 19 functions across 7 files. (6 skipped: 6 unsupported.)
Resolution
Write docstrings for the functions missing them to satisfy the coverage threshold.
Finishing Touches
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Review comment at @cpp/tests/unit_tests/multi_gpu/CMakeLists.txt around lines 1
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Update the SPDX-FileCopyrightText year range in the CMake file header from
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List each TensorRT-LLM component separately and apply the whole-archive link expression in a foreach loop. Preserve the existing component order and private link visibility.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move cudaProfilerUtils.cpp from common_src into the focused static
tllm_common_profiler library, exposed as tllm::common_profiler. Its explicit
logging dependency supplies environment parsing and error reporting without
pulling in the residual common object library or the full inference stack.
Link the component into the product with whole-archive semantics and a link
feature override so the previously exported implementation remains present.
Register cudaProfilerUtilsTest with explicit component dependencies, the
common owner aggregate, and host scheduling labels instead of FULL_STACK.
Validation:
- Built cudaProfilerUtilsTest through the configured project with Ninja.
- Passed the existing test covering eight environment parsing scenarios,
including deprecated-variable fallback and current-variable precedence.
- Checked the leaf graph excludes libtensorrt_llm, Torch, and residual common,
runtime, and kernel object libraries.
- Verified cudaProfilerUtils.cpp has exactly one production compile command,
owned by tllm_common_profiler.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move workerPool.cpp out of runtime_src into tllm_runtime_worker_pool,
exposed as tllm::runtime_worker_pool. Publish the headers and thread usage
requirements, and keep logging and CUDA runtime implementation dependencies
private. The component needs no common CUDA implementation or inference
backend to provide host task scheduling and optional CUDA device selection.
Whole-archive the component in the product and add its link feature override
to retain the former runtime object library's exported worker pool symbols.
Give workerPoolTest an explicit library dependency, runtime owner aggregate,
and host labels. Its existing tests use the default deviceId of -1.
Validation:
- Built workerPoolTest in the configured project and passed all 66 existing
cases, including void results and the 64 task-count/worker-count pairs.
- Built both workerPoolTest and cudaProfilerUtilsTest in the independent
project build tree, which contains no libtensorrt_llm.so.
- Checked both trees' leaf graphs exclude the product, Torch, and residual
common, runtime, and kernel object libraries; the worker leaf also avoids
common CUDA implementation linkage.
- Verified unique production ownership for both extracted implementations,
component aggregate membership, and host discovery properties.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move utils/numpyUtils.cpp from runtime_src into tllm_runtime_numpy,
exposed as tllm::runtime_numpy. Publish runtime_buffers as its explicit
usage requirement because the public I/O interface exposes BufferManager
and ITensor. Compile the production implementation once with C++20 and
position-independent code.
Whole-archive the component into the product and add the corresponding
link feature override to preserve all previously exported I/O symbols.
Migrate utilsTest from FULL_STACK to the focused component and runtime
owner aggregate. Label it as GPU-dependent and acquire the GPU resource
lock: the shared fixture queries CUDA and creates a stream even for its
CPU tensor cases.
Validation:
- Built and linked utilsTest with the configured CUDA/MPI/Torch project.
- Discovered all three existing tests without running GPU setup.
- Verified the leaf graph excludes libtensorrt_llm, Torch, and residual
runtime, common, and kernel object libraries.
- Verified numpyUtils.cpp has one production compilation owner and checked
runtime aggregate membership, GPU labels, and the GPU resource lock.
- GPU execution was unavailable in this environment.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move moeLoadBalancer/gdrwrap.cpp out of runtime_src into tllm_runtime_gdr,
exposed as tllm::runtime_gdr. Publish logging and CUDA runtime dependencies
used by its header and allocation helpers, and declare thread and dynamic
loader dependencies privately. Preserve dynamic loading of libgdrapi and
the existing Windows header stubs without introducing a mandatory GDRCopy
SDK or library dependency.
Whole-archive the component in the product with a link feature override to
retain its previously exported symbols. Give gdrcopyTest an explicit
component dependency and runtime owner aggregate instead of FULL_STACK.
Add GPU labels and a resource lock for its mapped-memory lifecycle tests.
Validation:
- Built and linked gdrcopyTest through the configured project.
- Discovered both existing lifecycle cases without invoking GPU setup.
- Checked the leaf graph excludes libtensorrt_llm, Torch, and residual common,
runtime, and kernel object libraries.
- Verified gdrwrap.cpp has exactly one production compilation owner and
checked runtime aggregate membership, GPU labels, and the resource lock.
- GPU and GDRCopy execution was unavailable in this environment.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move locality_domain/locality_domain_utils.cpp from runtime_src into the
focused tllm_runtime_locality library, exposed as tllm::runtime_locality.
Declare common CUDA utilities and the CUDA driver as public usage
requirements, and threads privately. Use C++20 and position-independent
code for the extracted implementation.
Whole-archive the component into the shared product with a link feature
override, retaining the previously exported locality-domain implementation.
Register localizationTest against the component rather than FULL_STACK,
add it to runtime-tests, and declare GPU labels and a resource lock.
Preserve the existing CUDA locality capability checks and disabled
performance cases.
Validation:
- Built and linked localizationTest with the configured project and
discovered its five correctness cases and six disabled performance cases.
- Built utilsTest, gdrcopyTest, and localizationTest in the independent
project tree without any existing libtensorrt_llm.so.
- Verified all three independent leaf graphs exclude the inference shared
library, Torch, and residual runtime, common, and kernel object libraries.
- Checked unique production source ownership, runtime aggregate membership,
GPU labels/resource locks, and discovery for all three extracted families.
- Confirmed both generated product link rules retain the three component
archives with whole-archive linkage.
- GPU execution was unavailable in this environment.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move the existing ipc_nvls_memory_src definition into the runtime owner
directory and expose it as tllm::runtime_ipc_nvls. Move ipcSocket.cpp and
mcastGroupComm.cpp from runtime_src into that archive so memory allocation,
POSIX handle exchange, and MPI multicast collectives have one explicit
production owner.
Declare common CUDA, CUDA driver, and runtime distributed dependencies,
plus conditional NCCL and NVSHMEM backend linkage. Use C++20/CUDA20 and
retain position-independent code and CUDA device-symbol resolution.
Whole-archive the component in the product with a link feature override to
retain the previously exported socket and multicast implementations.
Migrate ipcNvlsMemoryTest from FULL_STACK to the focused component, register
it in runtime-tests, and add GPU scheduling labels and a GPU resource lock.
Keep the existing archive target name for fused GEMM/all-reduce consumers.
Validation:
- Built and linked ipcNvlsMemoryTest with MPI enabled and NVSHMEM disabled.
- Discovered both static-capability and fabric-refinement regression tests.
- Verified the leaf graph excludes libtensorrt_llm, Torch, and residual
runtime, common, and kernel object libraries.
- Verified all three implementation sources have exactly one compilation
owner and checked runtime aggregate membership and GPU properties.
- GPU execution and NVSHMEM-enabled validation were unavailable here.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Replace th_utils' public libtensorrt_llm dependency with its actual runtime
buffer, Torch, and Python requirements. Expose tllm::torch_utils while
keeping the existing th_utils target name for Torch operator consumers.
Declare C++20 explicitly, preserve position-independent code, and remove
unused CUDA device-symbol resolution and direct cuBLAS/cuRAND linkage from
this C++ tensor-conversion utility library.
Migrate thUtilsTest from FULL_STACK and follow-up public linkage to explicit
private linkage through add_tllm_gtest. Register it in runtime-tests and
label it unit/runtime/thop/host: both existing cases create CPU tensors.
Python3::Python also supplies the public Python headers required by the
Torch extension interface.
Validation:
- Built thUtilsTest and passed both 1D and 2D shape-conversion cases.
- Independently built ipcNvlsMemoryTest and thUtilsTest in a project tree
containing no libtensorrt_llm.so; repeated Torch CPU tests there successfully.
- Verified both leaf graphs exclude the inference product and residual
common, runtime, kernel, and Torch operator object libraries.
- Checked unique production source ownership, runtime aggregate membership,
discovery, and host/GPU scheduling properties in both project trees.
- Confirmed both product link rules retain the IPC/NVLS component with
whole-archive semantics. IPC/NVLS GPU execution was unavailable here.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move genUniqueAgentName from the transport connection implementation into
agentName.cpp and expose its declaration through a lightweight agentName.h.
Keep connection.h including that header so existing callers retain the same
function declaration, symbol, name format, process suffix, and atomic counter.
The naming test now includes the lightweight header directly.
Add tllm_executor_agent_name, exposed as tllm::executor_agent_name, with
explicit header/thread requirements, C++20, and position-independent code.
Declare the executor backend's dependency on the component and whole-archive
it in the product with a link feature override to preserve symbol exports.
Migrate genUniqueAgentNameTest from FULL_STACK to the naming component and
Threads::Threads, remove Python linkage, and register executor/host ownership
and scheduling properties.
Validation:
- Built the isolated test and recompiled the production connection consumer.
- Passed all seven existing cases, including stable process identity, counter
progression, 1,000 serial names, and 4,000 names from eight concurrent threads.
- Verified the leaf graph excludes the product, Python, Torch, CUDA runtime,
and residual executor, batch-manager, runtime, common, and kernel libraries.
- Checked unique production source ownership, executor aggregate membership,
host discovery properties, and whole-archive product retention.
- Confirmed the naming archive defines the symbol and the recompiled
connection consumer references it without defining another copy.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move ContextTransferVoteReducer methods into contextTransferVoteReducer.cpp
while preserving the existing header declarations, validation, timeout
semantics, and exported method signatures. Keep the asynchronous MPI
coordinator implementation in contextTransferCoordinator.cpp.
Add tllm_context_transfer_consensus, exposed as
tllm::context_transfer_consensus, with only common error utilities as its
explicit dependency. Declare C++20, position-independent code, and standard
C++ mode. Link the component from the batch-manager backend and whole-archive
it in the product with a link feature override to preserve exported symbols.
Migrate contextTransferCoordinatorTest to the consensus component and
batch-manager/host ownership and discovery properties. Its existing cases
exercise the reducer and require neither MPI transport nor CUDA execution.
Validation:
- Built the standalone consensus test and recompiled the production MPI
coordinator implementation against the moved reducer methods.
- Passed all eight existing cases covering participant quorum, failure
precedence, immutable votes, interleaved requests, invalid inputs, timeout
publication, duplicate timeouts, and timeout-before-final-failure behavior.
- Independently built both host extractions in the separate project tree
without libtensorrt_llm.so and passed all 15 naming/consensus cases there.
- Checked both trees' test graphs exclude the inference product, Python,
Torch, CUDA runtime, and residual backend and object libraries.
- Verified unique production ownership, owner aggregate membership, host
discovery properties, and whole-archive product export retention.
- Confirmed the consensus archive defines the reducer method and the
recompiled coordinator references it without providing a duplicate.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
…ponent
Move loraModule.cpp and loraUtils.cpp from runtime_src into the focused
tllm_runtime_lora library, exposed as tllm::runtime_lora. Declare buffer
and distributed-runtime usage requirements for tensor validation, module
configuration, and WorldConfig callers, with C++20 and position-independent
code. Each existing implementation remains compiled once.
Whole-archive the component in the product with a link feature override to
retain all previously exported LoRA utility and module symbols. Migrate
loraUtilsTest from FULL_STACK to the explicit component, register it in
runtime-tests, and add GPU scheduling labels and a resource lock. Its fixture
creates a CUDA stream and its memory-type validation case allocates GPU
weights even though request validation also handles CPU tensors.
Validation:
- Built and linked loraUtilsTest through the configured CUDA/MPI project.
- Discovered all three existing request-validation cases.
- Checked the leaf graph excludes libtensorrt_llm, Torch, residual common,
runtime, and kernel objects, and the executor/batch-manager backends.
- Verified unique compilation ownership for both moved sources, runtime
aggregate membership, GPU discovery properties, and whole-archive retention.
- GPU execution was unavailable in this environment.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move loraCache.cpp from runtime_src into tllm_runtime_lora_cache, exposed as
tllm::runtime_lora_cache. Depend publicly on the LoRA module/validation
component and privately on threads for synchronized cache storage. Use
C++20 and position-independent code, retaining one production compilation
owner for the cache implementation.
Whole-archive the cache component in the shared product with a link feature
override to preserve the formerly exported runtime object-library symbols.
Migrate loraCacheTest from FULL_STACK to explicit cache and NumPy I/O
components. NumPy is a test fixture dependency rather than a cache-library
requirement. Register runtime ownership, GPU labels, and a resource lock.
Validation:
- Built and linked loraCacheTest through the configured project and
discovered all ten existing cases, including both parameter values for
each tensor-parallel copy-to-pages scenario.
- Built loraUtilsTest and loraCacheTest independently in the separate project
tree without an existing libtensorrt_llm.so; discovered all 13 cases there.
- Verified both leaf graphs exclude the inference shared library, Torch,
residual common/runtime/kernel object libraries, and executor/batch-manager
backend archives.
- Checked unique production ownership for LoRA modules, validation, and cache
storage, owner aggregates, GPU discovery properties, and whole-archive
product retention in both build trees.
- GPU execution was unavailable in this environment.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move utils/runtimeUtils.cpp from runtime_src into tllm_runtime_utils,
exposed as tllm::runtime_utils. Declare runtime buffer and distributed
usage requirements for the public tensor-map and WorldConfig interfaces,
plus C++20 and position-independent code. Keep all four implementations
and their public declarations unchanged.
Whole-archive the component in the product with a link feature override to
retain the previously exported device-selection, engine-loading, and
tensor-map helper symbols. This gives the PEFT cache manager an explicit
runtime utility dependency without linking the residual runtime objects.
Validation:
- Built the focused archive through the configured CUDA/MPI project.
- Verified runtimeUtils.cpp has exactly one production compilation owner.
- Checked its graph excludes the inference shared library, Torch, residual
common/runtime/kernel objects, and executor/batch-manager backend archives.
- Confirmed all four public implementations are defined by the new archive
and the generated product link rule retains it with whole-archive linkage.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Move peftCacheManager.cpp from the batch-manager backend archive into
tllm_peft_cache, exposed as tllm::peft_cache. Publish its LoRA cache,
request/KV-cache, and worker-pool usage requirements; keep NumPy I/O and
runtime device-selection helpers as private implementation dependencies.
Declare C++20, standard C++ mode, and position-independent code.
Link the new component from the batch-manager backend and whole-archive it
in the shared product with a link feature override to retain previously
exported PEFT implementations. Preserve all cache behavior and public
header declarations without recompiling the implementation in consumers.
Migrate peftCacheManagerTest from FULL_STACK to explicit PEFT and NumPy
fixture dependencies. Register it in batch-manager-tests with GPU labels
and a GPU resource lock because its fixtures create streams, device caches,
and worker pools that select a CUDA device.
Validation:
- Built and linked peftCacheManagerTest in the configured project.
- Discovered all 13 existing cases, including adapter validation, homogeneous
dtype selection, byte-budget/page-capacity calculations, cache operations,
task state, and prefetch coverage.
- Built the leaf independently in the separate project tree without an
existing libtensorrt_llm.so and repeated discovery there.
- Verified both trees' graphs exclude the inference shared library, Torch,
residual common/runtime/kernel objects, and executor/batch-manager backends.
- Checked unique compilation ownership for runtimeUtils.cpp and
peftCacheManager.cpp, archive symbols, whole-archive export retention,
batch-manager aggregate membership, and GPU discovery properties.
- GPU execution was unavailable in this environment.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
…mponent
hostAccessibleDeviceAllocatorTest only needs host-accessible GPU memory,
its topology support, and the existing GDR wrapper. Linking the complete
TensorRT-LLM shared library unnecessarily pulls in unrelated runtime,
executor, batch-manager, and kernel implementations.
Create tllm::runtime_host_accessible_memory with explicit ownership of
hostAccessibleDeviceAllocator.cpp and topologyDetector.cpp. Declare GDR,
threading, NUMA, and environment dependencies on the component, including
public NUMA usage requirements for the topology header. Remove both
sources from runtime_src and declare the remaining load-balancer
implementation's dependency on the extracted component.
Retain the component's symbols in the product shared library through
WHOLE_ARCHIVE and the corresponding link override. Register the allocator
test with the runtime owner aggregate, component-local linkage, GPU labels,
and the GPU resource lock while preserving its existing cases.
Validation: build the test in the primary and independent CUDA 13 / SM80
CMake trees; discover all five cases in both trees. Check source ownership,
archive symbols, product whole-archive retention, runtime aggregate
membership, GPU properties, and dependency graphs without the full shared
library, Torch, or residual runtime/kernel objects. The independent tree
does not contain libtensorrt_llm.so. GPU execution requires hardware that
is unavailable in this workspace.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Remove topologyDetector.cpp from the host-accessible memory archive and declare a public dependency on tllm::runtime_topology. This preserves transitive topology linkage for component consumers while giving TopologyDetector a single owning archive, avoiding duplicate definitions when the product library links both components with WHOLE_ARCHIVE.
Validation: bash run/run_build_wheel.sh --job_count 68 completed successfully, including libtensorrt_llm.so linkage and editable wheel installation. Confirmed the host-accessible memory archive contains only hostAccessibleDeviceAllocator.cpp.o; git diff --check passed.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
serializeUtilsTest covers executor values and cache-transfer metadata, but
its FULL_STACK link forced unrelated transport backends, Torch bindings,
and the complete TensorRT-LLM library into a host-only unit test build.
Two small metadata implementations were embedded in transport sources,
preventing the test from using the existing focused component libraries.
Move MemoryDesc serialization from the agent connection implementation to
memoryDesc.cpp and RequestInfo construction, comparison, accessors, and
serialization from dataTransceiver.cpp to requestInfo.cpp. Preserve the
method bodies, public declarations, and wire format. Give the new files
single ownership in tllm::executor_memory_desc and tllm::batch_request_info
with explicit dependencies, C++20, and position-independent code.
Declare the corresponding dependencies on the residual executor and
batch-manager targets. Retain the metadata symbols in the shared product
with WHOLE_ARCHIVE and link overrides, so existing transport consumers
continue to resolve the same methods.
Replace serializeUtilsTest's FULL_STACK linkage with executor value,
memory descriptor, request metadata, and distributed runtime components.
Register it in the executor owner aggregate with host labels. Retain the
Python dependency required by Pybind11-backed serialization headers and
declare it on the request metadata component as well.
Validation: build and pass all 49 existing serialization cases in both
the primary and independent CUDA 13 / SM80 CMake trees. Verify that the leaf
graph excludes libtensorrt_llm.so, Torch, process-group utilities,
and the residual runtime, kernel, executor, and batch-manager targets.
Check single source ownership, archive exports, product whole-archive
retention, executor aggregate membership, and host test properties. Compare
both extracted implementations with their original method bodies. Rebuild
both production transport consumer objects and verify they reference the
extracted metadata symbols without defining them. The independent tree
contains no libtensorrt_llm.so.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
userBufferTest exercises the user-buffer allocator and communicator, but
FULL_STACK linkage previously required the entire TensorRT-LLM product.
The production family was an object library whose dependency requirements
were supplied implicitly by the product build.
Convert userbuffers_src to a static library and expose it as
tllm::kernel_userbuffers. Replace recursive source globs with an explicit
six-source list for multi-device builds and preserve the two-source stub
branch when multi-device support is disabled. Declare CUDA common,
distributed runtime, CUDA driver, NCCL, environment, and threading
dependencies on the target. Retain the CUDA register limit and architecture
configuration, and require C++20/CUDA20 with resolved device symbols.
Move the component from ordinary product linkage to WHOLE_ARCHIVE and add
its link override, preserving the allocator, manager, communicator, and
kernel exports that the object library previously contributed.
Link userBufferTest directly to the user-buffer and distributed runtime
components. Add it to the kernel owner aggregate with user-buffer,
multi-GPU, and GPU labels plus the GPU resource lock. Preserve its existing
case and MPI-rank requirements.
Validation: build the leaf in the primary and independent CUDA 13 / SM80
CMake trees and discover UserBuffer.basic in each. Verify single ownership
of all six production sources, archive symbols, product whole-archive
retention, kernel aggregate membership, GPU properties, and graphs without
libtensorrt_llm.so, Torch, Python, or residual runtime, kernel, executor, and
batch-manager targets. The independent tree contains no libtensorrt_llm.so.
GPU/MPI execution is unverified because this workspace has no accessible
GPU hardware.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Dev Engineer Review
The change extracts profiler, runtime, executor, batch-manager, PEFT-cache, and user-buffer code into component libraries. It replaces broad shared-library dependencies with explicit links and updates unit-test registrations with component owners, dependencies, and scheduling labels.
Review risks include incomplete CMake dependencies, symbol retention, and configuration differences across CUDA, NCCL, NVSHMEM, Python, and NIXL builds. The explicit user-buffer source list also needs maintenance when sources change. No current review findings were supplied, so review finding counts are unavailable.
QA Engineer Review
The change updates C++ unit-test registrations under
cpp/tests/unit_tests/and changesgenUniqueAgentNameTest.cppto includeagentName.h. The registrations cover context-transfer vote reduction, PEFT caching, profiler utilities, serialization, agent-name generation, user buffers, runtime memory and utility components, and Torch utilities. The supplied evidence does not identify changes to test functions or IDs; the existing tests cover these behaviors.No matching entries for these C++ tests were found in the searched
tests/integration/test_lists/paths. Test execution results and coverage sufficiency are not established. The supplied CI notes report mixed outcomes and a multi-GPU approval-label requirement. Coverage verdict: needs follow-up.Per-File QA Perspective
cpp/tensorrt_llm/CMakeLists.txt: Whole-archive and link-library component sets change. Verify symbol retention and linkage in supported builds.cpp/tensorrt_llm/batch_manager/CMakeLists.txt: Adds libraries for PEFT caching, context-transfer consensus, and request information. Verify dependencies and downstream linkage.cpp/tensorrt_llm/batch_manager/contextTransferCoordinator.cpp: Removes the vote-reducer implementation. Verify coordinator behavior after the move.cpp/tensorrt_llm/batch_manager/contextTransferVoteReducer.cpp: Adds vote aggregation, conflict checks, timeout handling, and cleanup. Verify participant validation, duplicate votes, and readiness results.cpp/tensorrt_llm/batch_manager/dataTransceiver.cpp: RemovesRequestInfoimplementations. Verify consumers link to the extracted implementation.cpp/tensorrt_llm/batch_manager/requestInfo.cpp: Adds request metadata accessors and serialization. Verify round trips, field ordering, and equality behavior.cpp/tensorrt_llm/common/CMakeLists.txt: Extracts profiler utilities into a static library. Verify profiler consumers link without the shared library.cpp/tensorrt_llm/executor/CMakeLists.txt: Adds memory-descriptor and agent-name libraries. Verify component linkage.cpp/tensorrt_llm/executor/cache_transmission/agent_utils/agentName.cpp: Adds unique-name generation with host, process ID, random suffix, and counter. Verify uniqueness and thread safety.cpp/tensorrt_llm/executor/cache_transmission/agent_utils/agentName.h: Declares the name helper in a new header. Verify callers use the correct header and namespace.cpp/tensorrt_llm/executor/cache_transmission/agent_utils/connection.cpp: Removes moved name-generation and serialization implementations. Verify connection behavior and serialization linkage.cpp/tensorrt_llm/executor/cache_transmission/agent_utils/connection.h: Moves the name-helper declaration toagentName.h. Verify callers include the new header.cpp/tensorrt_llm/executor/memoryDesc.cpp: Adds memory-descriptor serialization. Verify field order and serialized-size agreement.cpp/tensorrt_llm/kernels/userbuffers/CMakeLists.txt: Changes user buffers to a static library with explicit sources and optional NCCL linkage. Verify single- and multi-device builds.cpp/tensorrt_llm/runtime/CMakeLists.txt: Splits runtime code into component libraries. Verify optional IPC/NVLS dependencies and linkage across build configurations.cpp/tensorrt_llm/thop/CMakeLists.txt: Decouples Torch utilities from the shared library. Verify Python- and Torch-enabled builds.cpp/tests/unit_tests/batch_manager/CMakeLists.txt: Registers context-transfer and PEFT-cache tests with component libraries. Verify dependencies and host/GPU scheduling.cpp/tests/unit_tests/common/CMakeLists.txt: Changes profiler-test ownership and labels. Verify the test’s component linkage and scheduling.cpp/tests/unit_tests/executor/CMakeLists.txt: Updates serialization and agent-name test dependencies and labels. Verify both tests in their configured environments.cpp/tests/unit_tests/executor/genUniqueAgentNameTest.cpp: Includes the new agent-name header. Existing tests cover name format, suffix stability, counter increments, uniqueness, and thread safety.cpp/tests/unit_tests/multi_gpu/CMakeLists.txt: Registers the user-buffer test with focused libraries and multi-GPU labels. Verify scheduling and optional NCCL linkage.cpp/tests/unit_tests/runtime/CMakeLists.txt: Updates runtime test links and host/GPU labels. Verify GPU requirements and discovery on applicable workers.cpp/tests/unit_tests/thop/CMakeLists.txt: Registers the Torch utility test throughtllm::torch_utils. Verify registration and linkage whenBUILD_PYTis enabled.Description
Refactor C++ build dependencies and test registration so more unit tests can build independently of libtensorrt_llm.so.
add_tllm_gtestwith explicit component dependencies, owners, and scheduling labels. Tests requiring the full library are explicitly markedFULL_STACK.Test Coverage
PR Checklist
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PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (see test instructions)
If PR introduces API changes, an appropriate PR label is added - either
api-compatibleorapi-breaking. Forapi-breaking, includeBREAKINGin the PR title.Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
Update tava architecture diagram if there is a significant design change in PR.
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Please check this after reviewing the above items as appropriate for this PR.
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