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CUPTI (PDF) - v11.7 (older) - Last updated June 06, 2022 - Send Feedback -

## 1. Release Notes

CUPTI Release Notes.

Release notes, including new features and important bug fixes. Supported platforms and GPUs.

### Release Notes

#### 1.1.1. Updates in CUDA 11.7 Update 1

Resolved Issues

- Resolved an issue for PC Sampling API `cuptiPCSamplingGetData` which might not always return all the samples when called after the PC sampling range defined by using the APIs `cuptiPCSamplingStart` and `cuptiPCSamplingStop`. Remaining samples were delivered in the successive call of the API `cuptiPCSamplingGetData` after the next range.

#### 1.1.2. Updates in CUDA 11.7

New Features

- A new activity kind `CUPTI_ACTIVITY_KIND_GRAPH_TRACE` and activity record `CUpti_ActivityGraphTrace` are introduced to represent the execution for a graph without giving visibility about the execution of its nodes. This is intended to reduce overheads involved in tracing each node separately. This activity can only be enabled for drivers of version 515 and above.
- A new API `cuptiActivityEnableAndDump` is added to provide snapshot of certain activities like device, context, stream, NVLINK and PCIE at any point during the profiling session.
- Added sample cupti_correlation to show correlation between CUDA APIs and corresponding GPU activities.
- Added sample cupti_trace_injection to show how to build an injection library using the activity and callback APIs which can be used to trace any CUDA application.

Resolved Issues

- Fixed corruption in the function name for PC Sampling API records.
- Fixed incorrect timestamps for GPU activities when user calls the API `cuptiActivityRegisterTimestampCallback` in the late CUPTI attach scenario.
- Fixed incomplete records for device to device memcopies in the late CUPTI attach scenario. This issue manifests mainly when application has a mix of CUDA graph and normal kernel launches.

#### 1.1.3. Updates in CUDA 11.6 Update 1

Resolved Issues

- Fixed hang for the PC Sampling API `cuptiPCSamplingStop`. This issue is seen for the PC sampling start and stop resulting in generation of large number of sampling records.
- Fixed timing issue for specific device to device memcpy operations.

#### 1.1.4. Updates in CUDA 11.6

New Features

- Two new fields `channelID` and `channelType` are added in the activity records for kernel, memcpy, peer-to-peer memcpy and memset to output the ID and type of the hardware channel on which these activities happen. Activity records `CUpti_ActivityKernel6`, `CUpti_ActivityMemcpy4`, `CUpti_ActivityMemcpyPtoP3` and `CUpti_ActivityMemset3` are deprecated and replaced by new activity records `CUpti_ActivityKernel7`, `CUpti_ActivityMemcpy5`, `CUpti_ActivityMemcpyPtoP4` and `CUpti_ActivityMemset4`.
- New fields `isMigEnabled`, `gpuInstanceId`, `computeInstanceId` and `migUuid` are added in the device activity record to provide MIG information for the MIG enabled GPU. Activity record `CUpti_ActivityDevice3` is deprecated and replaced by a new activity record `CUpti_ActivityDevice4`.
- A new field `utilizedSize` is added in the memory pool activity record to provide the utilized size of the memory pool. Activity record `CUpti_ActivityMemoryPool` is deprecated and replaced by a new activity record `CUpti_ActivityMemoryPool2`.
- API `cuptiActivityRegisterTimestampCallback` and callback function `CUpti_TimestampCallbackFunc` are added to register a callback function to obtain timestamp of user's choice instead of using CUPTI provided timestamp in activity records.
- Profiling API supports profiling OptiX application.

Resolved Issues

- Fixed multi-pass metric collection using the Profiling API in the auto range and kernel replay mode for Cuda Graph.
- Fixed the performance issue for the PC sampling API `cuptiPCSamplingStop`.
- Fixed corruption in variable names for OpenACC activity records.

#### 1.1.5. Updates in CUDA 11.5 Update 1

Resolved Issues

- Resolved an issue that causes incorrect range name for NVTX event attributes. The issue was introduced in CUDA 11.4.
- Made NVTX initialization APIs `InitializeInjectionNvtx` and `InitializeInjectionNvtx2` thread-safe.

#### 1.1.6. Updates in CUDA 11.5

New Features

- A new API `cuptiProfilerDeviceSupported` is introduced to expose overall Profiling API support and specific requirements for a given device. Profiling API must be initialized by calling `cuptiProfilerInitialize` before testing device support.
- PC Sampling struct `CUpti_PCSamplingData` introduces a new field `nonUsrKernelsTotalSamples` to provide information about the number of samples collected for all non-user kernels.
- Activity record `CUpti_ActivityDevice2` for device information has been deprecated and replaced by a new activity record `CUpti_ActivityDevice3`. New record adds a flag `isCudaVisible` to indicate whether device is visible to CUDA.
- Activity record `CUpti_ActivityNvLink3` for NVLINK information has been deprecated and replaced by a new activity record `CUpti_ActivityNvLink4`. New record can accommodate NVLINK port information upto a maximum of 32 ports.
- A new CUPTI Checkpoint API is introduced, enabling automatic saving and restoring of device state, and facilitating development of kernel replay tools. This is helpful for User Replay mode of the CUPTI Profiling API, but is not limited to use with CUPTI.
- Tracing is supported on the Windows Subsystem for Linux version 2 (WSL2).
- CUPTI is not supported on NVIDIA Crypto Mining Processors (CMP). A new error code `CUPTI_ERROR_CMP_DEVICE_NOT_SUPPORTED` is introduced to indicate it.

Resolved Issues

- Resolved an issue that causes crash for tracing of device to device memcopy operations.
- Resolved an issue that causes crash for OpenACC activity when it is enabled before other activities.

#### 1.1.7. Updates in CUDA 11.4 Update 1

Resolved Issues

- Resolved serialization of CUDA Graph launches for applications which use multiple threads to launch work.
- Previously, for applications that use CUDA Dynamic Parallelism (CDP), CUPTI detects the presence of the CDP kernels in the CUDA module. Even if CDP kernels are not called, it fails to trace the application. There is a change in the behavior, CUPTI now traces all the host launched kernels until it encounters a host launched kernel which launches child kernels. Subsequent kernels are not traced.

#### 1.1.8. Updates in CUDA 11.4

New Features

- Profiling APIs support profiling of the CUDA kernel nodes launched by a CUDA Graph. Auto range profiling with kernel replay mode and user range profiling with user replay and application replay modes are supported. Other combinations of range profiling and replay modes are not supported.
- Added support for tracing and profiling on NVIDIA virtual GPUs (vGPUs) on an upcoming GRID/vGPU release.
- Added sample profiling_injection to show how to build injection library using the Profiling API.
- Added sample concurrent_profiling to show how to retain the kernel concurrency across streams and devices using the Profiling API.

Resolved Issues

- Resolved the issue of not tracing the device to device memcopy nodes in a CUDA Graph.
- Fixed the issue of reporting zero size for local memory pool for mempool creation record.
- Resolved the issue of non-collection of samples for the default CUDA context for PC Sampling API.
- Enabled tracking of all domains and registered strings in NVTX irrespective of whether the NVTX activity kind or callbacks are enabled. This state tracking is needed for proper working of the tool which creates these NVTX objects before enabling the NVTX activity kind or callback.

#### 1.1.9. Updates in CUDA 11.3

New Features

- A new set of CUPTI APIs for PC sampling data collection are provided in the header file `cupti_pcsampling.h` which support continuous mode data collection without serializing kernel execution and have a lower runtime overhead. Along with these a utility library is provided in the header file `cupti_pcsampling_util.h` which has APIs for GPU assembly to CUDA-C source correlation and for reading and writing the PC sampling data from/to files. Refer to the section CUPTI PC Sampling API for more details.
- Enum `CUpti_PcieGen` is extended to include PCIe Gen 5.
- The following functions are deprecated and will be removed in a future release:
  - Struct `NVPA_MetricsContext` and related APIs `NVPW_MetricsContext_*` from the header `nvperf_host.h`. It is recommended to use the struct `NVPW_MetricsEvaluator` and related APIs `NVPW_MetricsEvaluator_*` instead. Profiling API samples have been updated to show how to use these APIs.
  - `cuptiDeviceGetTimestamp` from the header `cupti_events.h`.

Resolved Issues

- Overhead reduction for tracing of CUDA memcopies.
- To provide normalized timestamps for all activities, CUPTI uses linear interpolation for conversion from GPU timestamps to CPU timestamps. This method can cause spurious gaps or overlap on the timeline. CUPTI improves the conversion function to provide more precise timestamps.
- Generate overhead activity record for semaphore pool allocation.

#### 1.1.10. Updates in CUDA 11.2

New Features

- A new activity kind `CUPTI_ACTIVITY_KIND_MEMORY_POOL` and activity record `CUpti_ActivityMemoryPool` are introduced to represent the creation, destruction and trimming of a memory pool. Enum `CUpti_ActivityMemoryPoolType` lists types of memory pool.
- A new activity kind `CUPTI_ACTIVITY_KIND_MEMORY2` and activity record `CUpti_ActivityMemory2` are introduced to provide separate records for memory allocation and release operations. This helps in correlation of records of these operations to the corresponding CUDA APIs, which otherwise is not possible using the existing activity record `CUpti_ActivityMemory` which provides a single record for both the memory operations.
- Added a new pointer field of type `CUaccessPolicyWindow` in the kernel activity record to provide the access policy window which specifies a contiguous region of global memory and a persistence property in the L2 cache for accesses within that region. To accomodate this change, activity record `CUpti_ActivityKernel5` is deprecated and replaced by a new activity record `CUpti_ActivityKernel6`. This attribute is not collected by default. To control the collection of launch attributes, a new API `cuptiActivityEnableLaunchAttributes` is introdcued.
- New attributes `CUPTI_ACTIVITY_ATTR_DEVICE_BUFFER_PRE_ALLOCATE_VALUE` and `CUPTI_ACTIVITY_ATTR_PROFILING_SEMAPHORE_PRE_ALLOCATE_VALUE` are added in the activity attribute enum `CUpti_ActivityAttribute` to set and get the number of device buffers and profiling semaphore pools which are preallocated for the context.
- CUPTI now allocates profiling buffer for concurrent kernel tracing in the pinned host memory in place of device memory. This might help in improving the performance of the tracing run. Memory location can be controlled using the attribute `CUPTI_ACTIVITY_ATTR_MEM_ALLOCATION_TYPE_HOST_PINNED` of the activity attribute enum `CUpti_ActivityAttribute`.
- The compiler generated line information for inlined functions is improved due to which CUPTI can associate inlined functions with the line information of the function call site that has been inlined.
- Removed support for NVLink performance metrics (`nvlrx__*` and `nvltx__*`) from the Profiling API due to a potential application hang during data collection. The metrics will be added back in a future CUDA release.

Resolved Issues

- Execution overheads introduced by CUPTI in the tracing path is reduced.
- For the concurrent kernel activity kind `CUPTI_ACTIVITY_KIND_CONCURRENT_KERNEL`, CUPTI instruments the kernel code to collect the timing information. Previously, every kernel in the CUDA module was instrumented, thus the overhead is proportional to the number of different kernels in the module. This is a static overhead which happens at the time of loading the CUDA module. To reduce this overhead, kernels are not instrumented at the module load time, instead a single instrumentation code is generated at the time of loading the CUDA module and it is applied to each kernel during the kernel execution, thus avoiding most of the static overhead at the CUDA module load time.

#### 1.1.11. Updates in CUDA 11.1

New Features

- CUPTI adds tracing and profiling support for the NVIDIA Ampere GPUs with compute capability 8.6.
- Added a new field `graphId` in the activity records for kernel, memcpy, peer-to-peer memcpy and memset to output the unique ID of the CUDA graph that launches the activity through CUDA graph APIs. To accomodate this change, activity records `CUpti_ActivityMemcpy3`, `CUpti_ActivityMemcpyPtoP2` and `CUpti_ActivityMemset2` are deprecated and replaced by new activity records `CUpti_ActivityMemcpy4`, `CUpti_ActivityMemcpyPtoP3` and `CUpti_ActivityMemset3`. And kernel activity record `CUpti_ActivityKernel5` replaces the padding field with `graphId`. Added a new API `cuptiGetGraphId` to query the unique ID of the CUDA graph.
- Added a new API `cuptiActivityFlushPeriod` to set the flush period for the worker thread.
- Added support for profiling cooperative kernels using Profiling APIs.
- Added NVLink performance metrics (nvlrx__* and nvltx__*) using the Profiling APIs. These metrics are available on devices with compute capability 7.0, 7.5 and 8.0, and these can be collected at the context level. Refer to the table Metrics Mapping Table for mapping between earlier CUPTI metrics and the Perfworks NVLink metrics for devices with compute capability 7.0.

Resolved Issues

- Resolved an issue that causes CUPTI to not return full and completed activity buffers for a long time, CUPTI now attempts to return buffers early.
- To reduce the runtime overhead, CUPTI wakes up the worker thread based on certain heuristics instead of waking it up at a regular interval. New API `cuptiActivityFlushPeriod` can be used to control the flush period of the worker thread. This setting overrides the CUPTI heurtistics.

#### 1.1.12. Updates in CUDA 11.0

New Features

- CUPTI adds tracing and profiling support for devices with compute capability 8.0 i.e. NVIDIA A100 GPUs and systems that are based on A100.
- Enhancements for CUDA Graph:
  - Support to correlate the CUDA Graph node with the GPU activities: kernel, memcpy, memset.
    - Added a new field `graphNodeId` for Node Id in the activity records for kernel, memcpy, memset and P2P transfers. Activity records `CUpti_ActivityKernel4`, `CUpti_ActivityMemcpy2`, `CUpti_ActivityMemset` and `CUpti_ActivityMemcpyPtoP` are deprecated and replaced by new activity records `CUpti_ActivityKernel5`, `CUpti_ActivityMemcpy3`, `CUpti_ActivityMemset2` and `CUpti_ActivityMemcpyPtoP2`.
    - `graphNodeId` is the unique ID for the graph node.
    - `graphNodeId` can be queried using the new CUPTI API `cuptiGetGraphNodeId()`.
    - Callback `CUPTI_CBID_RESOURCE_GRAPHNODE_CREATED` is issued between a pair of the API enter and exit callbacks.
  - Introduced new callback `CUPTI_CBID_RESOURCE_GRAPHNODE_CLONED` to indicate the cloning of the CUDA Graph node.
  - Retain CUDA driver performance optimization in case memset node is sandwiched between kernel nodes. CUPTI no longer disables the conversion of memset nodes into kernel nodes for CUDA graphs.
  - Added support for cooperative kernels in CUDA graphs.
- Added support to trace Optix applications. Refer the Optix Profiling section.
- CUPTI overhead is associated with the thread rather than process. Object kind of the overhead record `CUpti_ActivityOverhead` is switched to `CUPTI_ACTIVITY_OBJECT_THREAD`.
- Added error code `CUPTI_ERROR_MULTIPLE_SUBSCRIBERS_NOT_SUPPORTED` to indicate the presense of another CUPTI subscriber. API `cuptiSubscribe()` returns the new error code than `CUPTI_ERROR_MAX_LIMIT_REACHED`.
- Added a new enum `CUpti_FuncShmemLimitConfig` to indicate whether user has opted in for maximun dynamic shared memory size on devices with compute capability 7.x by using function attributes `CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES` or `cudaFuncAttributeMaxDynamicSharedMemorySize` with CUDA driver and runtime respectively. Field `shmemLimitConfig` in the kernel activity record `CUpti_ActivityKernel5` shows the user choice. This helps in correct occupancy calulation. Value `FUNC_SHMEM_LIMIT_OPTIN` in the enum `cudaOccFuncShmemConfig` is the corresponding option in the CUDA occupancy calculator.

Resolved Issues

- Resolved an issue that causes incorrect or stale timing for memcopy and serial kernel activities.
- Overhead for PC Sampling Activity APIs is reduced by avoiding the reconfiguration of the GPU when PC sampling period doesn't change between successive kernels. This is applicable for devices with compute capability 7.0 and higher.
- Fixed issues in the API `cuptiFinalize()` including the issue which may cause the application to crash. This API provides ability for safe and full detach of CUPTI during the execution of the application. More details in the section Dynamic Detach.

#### 1.1.13. Updates in CUDA 10.2

New Features

- CUPTI allows tracing features for non-root and non-admin users on desktop platforms. Note that events and metrics profiling is still restricted for non-root and non-admin users. More details about the issue and the solutions can be found on this web page.
- CUPTI no longer turns off the performance characteristics of CUDA Graph when tracing the application.
- CUPTI now shows memset nodes in the CUDA graph.
- Fixed the incorrect timing issue for the asynchronous cuMemset/cudaMemset activity.
- Several performance improvements are done in the tracing path.

#### 1.1.14. Updates in CUDA 10.1 Update 2

New Features

- This release is focused on bug fixes and stability of the CUPTI.
- A security vulnerability issue required profiling tools to disable all the features for non-root or non-admin users. As a result, CUPTI cannot profile the application when using a Windows 419.17 or Linux 418.43 or later driver. More details about the issue and the solutions can be found on this web page.

#### 1.1.15. Updates in CUDA 10.1 Update 1

New Features

- Support for the IBM POWER platform is added for the
  - Profiling APIs in the header `cupti_profiler_target.h`
  - Perfworks metric APIs in the headers `nvperf_host.h` and `nvperf_target.h`

#### 1.1.16. Updates in CUDA 10.1

New Features

- This release is focused on bug fixes and performance improvements.
- The new set of profiling APIs and Perfworks metric APIs which were introduced in the CUDA Toolkit 10.0 are now integrated into the CUPTI library distributed in the CUDA Toolkit. Refer to the sections CUPTI Profiling API and Perfworks Metric APIs for documentation of the new APIs.
- Event collection mode `CUPTI_EVENT_COLLECTION_MODE_CONTINUOUS` is now supported on all device classes including Geforce and Quadro.
- Support for the NVTX string registration API `nvtxDomainRegisterStringA().`
- Added enum `CUpti_PcieGen` to list PCIE generations.

#### 1.1.17. Updates in CUDA 10.0

New Features

- Added tracing support for devices with compute capability 7.5.
- A new set of metric APIs are added for devices with compute capability 7.0 and higher. These provide low and deterministic profiling overhead on the target system. These APIs are currently supported only on Linux x86 64-bit and Windows 64-bit platforms. Refer to the CUPTI web page for documentation and details to download the package with support for these new APIs. Note that both the old and new metric APIs are supported for compute capability 7.0. This is to enable transition of code to the new metric APIs. But one cannot mix the usage of the old and new metric APIs.
- CUPTI supports profiling of OpenMP applications. OpenMP profiling information is provided in the form of new activity records `CUpti_ActivityOpenMp`. New API `cuptiOpenMpInitialize` is used to initialize profiling for supported OpenMP runtimes.
- Activity record for kernel `CUpti_ActivityKernel4` provides shared memory size set by the CUDA driver.
- Tracing support for CUDA kernels, memcpy and memset nodes launched by a CUDA Graph.
- Added support for resource callbacks for resources associated with the CUDA Graph. Refer enum `CUpti_CallbackIdResource` for new callback IDs.

#### 1.1.18. Updates in CUDA 9.2

New Features

- Added support to query PCI devices information which can be used to construct the PCIE topology. See activity kind `CUPTI_ACTIVITY_KIND_PCIE` and related activity record `CUpti_ActivityPcie`.
- To view and analyze bandwidth of memory transfers over PCIe topologies, new set of metrics to collect total data bytes transmitted and recieved through PCIe are added. Those give accumulated count for all devices in the system. These metrics are collected at the device level for the entire application. And those are made available for devices with compute capability 5.2 and higher.
- CUPTI added support for new metrics:
  - Instruction executed for different types of load and store
  - Total number of cached global/local load requests from SM to texture cache
  - Global atomic/non-atomic/reduction bytes written to L2 cache from texture cache
  - Surface atomic/non-atomic/reduction bytes written to L2 cache from texture cache
  - Hit rate at L2 cache for all requests from texture cache
  - Device memory (DRAM) read and write bytes
  - The utilization level of the multiprocessor function units that execute tensor core instructions for devices with compute capability 7.0
- A new attribute `CUPTI_EVENT_ATTR_PROFILING_SCOPE` is added under enum `CUpti_EventAttribute` to query the profiling scope of a event. Profiling scope indicates if the event can be collected at the context level or device level or both. See Enum `CUpti_EventProfilingScope` for avaiable profiling scopes.
- A new error code `CUPTI_ERROR_VIRTUALIZED_DEVICE_NOT_SUPPORTED` is added to indicate that tracing and profiling on virtualized GPU is not supported.

#### 1.1.19. Updates in CUDA 9.1

New Features

- Added a field for correlation ID in the activity record `CUpti_ActivityStream`.

#### 1.1.20. Updates in CUDA 9.0

New Features

- CUPTI extends tracing and profiling support for devices with compute capability 7.0.
- Usage of compute device memory can be tracked through CUPTI. A new activity record `CUpti_ActivityMemory` and activity kind `CUPTI_ACTIVITY_KIND_MEMORY` are added to track the allocation and freeing of memory. This activity record includes fields like virtual base address, size, PC (program counter), timestamps for memory allocation and free calls.
- Unified memory profiling adds new events for thrashing, throttling, remote map and device-to-device migration on 64 bit Linux platforms. New events are added under enum `CUpti_ActivityUnifiedMemoryCounterKind`. Enum `CUpti_ActivityUnifiedMemoryRemoteMapCause` lists possible causes for remote map events.
- PC sampling supports wide range of sampling periods ranging from 2^5 cycles to 2^31 cycles per sample. This can be controlled through new field `samplingPeriod2` in the PC sampling configuration struct `CUpti_ActivityPCSamplingConfig`.
- Added API `cuptiDeviceSupported()` to check support for a compute device.
- Activity record `CUpti_ActivityKernel3` for kernel execution has been deprecated and replaced by new activity record `CUpti_ActivityKernel4`. New record gives information about queued and submit timestamps which can help to determine software and hardware latencies associated with the kernel launch. These timestamps are not collected by default. Use API `cuptiActivityEnableLatencyTimestamps()` to enable collection. New field `launchType` of type `CUpti_ActivityLaunchType` can be used to determine if it is a cooperative CUDA kernel launch.
- Activity record `CUpti_ActivityPCSampling2` for PC sampling has been deprecated and replaced by new activity record `CUpti_ActivityPCSampling3`. New record accomodates 64-bit PC Offset supported on devices of compute capability 7.0 and higher.
- Activity record `CUpti_ActivityNvLink` for NVLink attributes has been deprecated and replaced by new activity record `CUpti_ActivityNvLink2`. New record accomodates increased port numbers between two compute devices.
- Activity record `CUpti_ActivityGlobalAccess2` for source level global accesses has been deprecated and replaced by new activity record `CUpti_ActivityGlobalAccess3`. New record accomodates 64-bit PC Offset supported on devices of compute capability 7.0 and higher.
- New attributes `CUPTI_ACTIVITY_ATTR_PROFILING_SEMAPHORE_POOL_SIZE` and `CUPTI_ACTIVITY_ATTR_PROFILING_SEMAPHORE_POOL_LIMIT` are added in the activity attribute enum `CUpti_ActivityAttribute` to set and get the profiling semaphore pool size and the pool limit.

#### 1.1.21. Updates in CUDA 8.0

New Features

- Sampling of the program counter (PC) is enhanced to point out the true latency issues, it indicates if the stall reasons for warps are actually causing stalls in the issue pipeline. Field `latencySamples` of new activity record `CUpti_ActivityPCSampling2` provides true latency samples. This field is valid for devices with compute capability 6.0 and higher. See section PC Sampling for more details.
- Support for NVLink topology information such as the pair of devices connected via NVLink, peak bandwidth, memory access permissions etc is provided through new activity record `CUpti_ActivityNvLink`. NVLink performance metrics for data transmitted/received, transmit/receive throughput and respective header overhead for each physical link. See section NVLink for more details.
- CUPTI supports profiling of OpenACC applications. OpenACC profiling information is provided in the form of new activity records `CUpti_ActivityOpenAccData`, `CUpti_ActivityOpenAccLaunch` and `CUpti_ActivityOpenAccOther`. This aids in correlating OpenACC constructs on the CPU with the corresponding activity taking place on the GPU, and mapping it back to the source code. New API `cuptiOpenACCInitialize` is used to initialize profiling for supported OpenACC runtimes. See section OpenACC for more details.
- Unified memory profiling provides GPU page fault events on devices with compute capability 6.0 and 64 bit Linux platforms. Enum `CUpti_ActivityUnifiedMemoryAccessType` lists memory access types for GPU page fault events and enum `CUpti_ActivityUnifiedMemoryMigrationCause` lists migration causes for data transfer events.
- Unified Memory profiling support is extended to Mac platform.
- Support for 16-bit floating point (FP16) data format profiling. New metrics inst_fp_16, flop_count_hp_add, flop_count_hp_mul, flop_count_hp_fma, flop_count_hp, flop_hp_efficiency, half_precision_fu_utilization are supported. Peak FP16 flops per cycle for device can be queried using the enum `CUPTI_DEVICE_ATTR_FLOP_HP_PER_CYCLE` added to `CUpti_DeviceAttribute`.
- Added new activity kinds `CUPTI_ACTIVITY_KIND_SYNCHRONIZATION`, `CUPTI_ACTIVITY_KIND_STREAM` and `CUPTI_ACTIVITY_KIND_CUDA_EVENT`, to support the tracing of CUDA synchronization constructs such as context, stream and CUDA event synchronization. Synchronization details are provided in the form of new activity record `CUpti_ActivitySynchronization`. Enum `CUpti_ActivitySynchronizationType` lists different types of CUDA synchronization constructs.
- APIs `cuptiSetThreadIdType()`/`cuptiGetThreadIdType()` to set/get the mechanism used to fetch the thread-id used in CUPTI records. Enum `CUpti_ActivityThreadIdType` lists all supported mechanisms.
- Added API `cuptiComputeCapabilitySupported()` to check the support for a specific compute capability by the CUPTI.
- Added support to establish correlation between an external API (such as OpenACC, OpenMP) and CUPTI API activity records. APIs `cuptiActivityPushExternalCorrelationId()` and `cuptiActivityPopExternalCorrelationId()` should be used to push and pop external correlation ids for the calling thread. Generated records of type `CUpti_ActivityExternalCorrelation` contain both external and CUPTI assigned correlation ids.
- Added containers to store the information of events and metrics in the form of activity records `CUpti_ActivityInstantaneousEvent`, `CUpti_ActivityInstantaneousEventInstance`, `CUpti_ActivityInstantaneousMetric` and `CUpti_ActivityInstantaneousMetricInstance`. These activity records are not produced by the CUPTI, these are included for completeness and ease-of-use. Profilers built on top of CUPTI that sample events may choose to use these records to store the collected event data.
- Support for domains and annotation of synchronization objects added in NVTX v2. New activity record `CUpti_ActivityMarker2` and enums to indicate various stages of synchronization object i.e. `CUPTI_ACTIVITY_FLAG_MARKER_SYNC_ACQUIRE`, `CUPTI_ACTIVITY_FLAG_MARKER_SYNC_ACQUIRE_SUCCESS`, `CUPTI_ACTIVITY_FLAG_MARKER_SYNC_ACQUIRE_FAILED` and `CUPTI_ACTIVITY_FLAG_MARKER_SYNC_RELEASE` are added.
- Unused field `runtimeCorrelationId` of the activity record `CUpti_ActivityMemset` is broken into two fields `flags` and `memoryKind` to indicate the asynchronous behaviour and the kind of the memory used for the memset operation. It is supported by the new flag `CUPTI_ACTIVITY_FLAG_MEMSET_ASYNC` added in the enum `CUpti_ActivityFlag`.
- Added flag `CUPTI_ACTIVITY_MEMORY_KIND_MANAGED` in the enum `CUpti_ActivityMemoryKind` to indicate managed memory.
- API `cuptiGetStreamId` has been deprecated. A new API `cuptiGetStreamIdEx` is introduced to provide the stream id based on the legacy or per-thread default stream flag.

#### 1.1.22. Updates in CUDA 7.5

New Features

- Device-wide sampling of the program counter (PC) is enabled by default. This was a preview feature in the CUDA Toolkit 7.0 release and it was not enabled by default.
- Ability to collect all events and metrics accurately in presence of multiple contexts on the GPU is extended for devices with compute capability 5.x.
- API `cuptiGetLastError` is introduced to return the last error that has been produced by any of the CUPTI API calls or the callbacks in the same host thread.
- Unified memory profiling is supported with MPS (Multi-Process Service)
- Callback is provided to collect replay information after every kernel run during kernel replay. See API `cuptiKernelReplaySubscribeUpdate` and callback type `CUpti_KernelReplayUpdateFunc`.
- Added new attributes in enum `CUpti_DeviceAttribute` to query maximum shared memory size for different cache preferences for a device function.

#### 1.1.23. Updates in CUDA 7.0

New Features

- CUPTI supports device-wide sampling of the program counter (PC). Program counters along with the stall reasons from all active warps are sampled at a fixed frequency in the round robin order. Activity record `CUpti_ActivityPCSampling` enabled using activity kind `CUPTI_ACTIVITY_KIND_PC_SAMPLING` outputs stall reason along with PC and other related information. Enum `CUpti_ActivityPCSamplingStallReason` lists all the stall reasons. Sampling period is configurable and can be tuned using API `cuptiActivityConfigurePCSampling`. This feature is available on devices with compute capability 5.2.
- Added new activity record `CUpti_ActivityInstructionCorrelation` which can be used to dump source locator records for all the PCs of the function.
- All events and metrics for devices with compute capability 3.x and 5.0 can be collected accurately in presence of multiple contexts on the GPU. In previous releases only some events and metrics could be collected accurately when multiple contexts were executing on the GPU.
- Unified memory profiling is enhanced by providing fine grain data transfers to and from the GPU, coupled with more accurate timestamps with each transfer. This information is provided through new activity record `CUpti_ActivityUnifiedMemoryCounter2`, deprecating old record `CUpti_ActivityUnifiedMemoryCounter`.
- MPS tracing and profiling support is extended on multi-gpu setups.
- Activity record `CUpti_ActivityDevice` for device information has been deprecated and replaced by new activity record `CUpti_ActivityDevice2`. New record adds device UUID which can be used to uniquely identify the device across profiler runs.
- Activity record `CUpti_ActivityKernel2` for kernel execution has been deprecated and replaced by new activity record `CUpti_ActivityKernel3`. New record gives information about Global Partitioned Cache Configuration requested and executed. Partitioned global caching has an impact on occupancy calculation. If it is ON, then a CTA can only use a half SM, and thus a half of the registers available per SM. The new fields apply for devices with compute capability 5.2 and higher. Note that this change was done in CUDA 6.5 release with support for compute capabilty 5.2.

#### 1.1.24. Updates in CUDA 6.5

New Features

- Instruction classification is done for source-correlated Instruction Execution activity `CUpti_ActivityInstructionExecution`. See `CUpti_ActivityInstructionClass` for instruction classes.
- Two new device attributes are added to the activity `CUpti_DeviceAttribute`:
  - `CUPTI_DEVICE_ATTR_FLOP_SP_PER_CYCLE` gives peak single precision flop per cycle for the GPU.
  - `CUPTI_DEVICE_ATTR_FLOP_DP_PER_CYCLE` gives peak double precision flop per cycle for the GPU.
- Two new metric properties are added:
  - `CUPTI_METRIC_PROPERTY_FLOP_SP_PER_CYCLE` gives peak single precision flop per cycle for the GPU.
  - `CUPTI_METRIC_PROPERTY_FLOP_DP_PER_CYCLE` gives peak double precision flop per cycle for the GPU.
- Activity record `CUpti_ActivityGlobalAccess` for source level global access information has been deprecated and replaced by new activity record `CUpti_ActivityGlobalAccess2`. New record additionally gives information needed to map SASS assembly instructions to CUDA C source code. And it also provides ideal L2 transactions count based on the access pattern.
- Activity record `CUpti_ActivityBranch` for source level branch information has been deprecated and replaced by new activity record `CUpti_ActivityBranch2`. New record additionally gives information needed to map SASS assembly instructions to CUDA C source code.
- Sample `sass_source_map` is added to demonstrate the mapping of SASS assembly instructions to CUDA C source code.
- Default event collection mode is changed to Kernel (`CUPTI_EVENT_COLLECTION_MODE_KERNEL`) from Continuous (`CUPTI_EVENT_COLLECTION_MODE_CONTINUOUS`). Also Continuous mode is supported only on Tesla devices.
- Profiling results might be inconsistent when auto boost is enabled. Profiler tries to disable auto boost by default, it might fail to do so in some conditions, but profiling will continue. A new API `cuptiGetAutoBoostState` is added to query the auto boost state of the device. This API returns error `CUPTI_ERROR_NOT_SUPPORTED` on devices that don't support auto boost. Note that auto boost is supported only on certain Tesla devices from the Kepler+ family.
- Activity record `CUpti_ActivityKernel2` for kernel execution has been deprecated and replaced by new activity record `CUpti_ActivityKernel3`. New record additionally gives information about Global Partitioned Cache Configuration requested and executed. The new fields apply for devices with 5.2 Compute Capability.

#### 1.1.25. Updates in CUDA 6.0

New Features

- Two new CUPTI activity kinds have been introduced to enable two new types of source-correlated data collection. The `Instruction Execution` kind collects SASS-level instruction execution counts, divergence data, and predication data. The `Shared Access` kind collects source correlated data indication inefficient shared memory accesses.
- CUPTI provides support for CUDA applications using Unified Memory. A new activity record reports Unified Memory activity such as transfers to and from a GPU and the number of Unified Memory related page faults.
- CUPTI recognized and reports the special MPS context that is used by CUDA applications running on a system with MPS enabled.
- The CUpti_ActivityContext activity record `CUpti_ActivityContext` has been updated to introduce a new field into the structure in a backwards compatible manner. The 32-bit `computeApiKind` field was replaced with two 16 bit fields, `computeApiKind` and `defaultStreamId`. Because all valid `computeApiKind` values fit within 16 bits, and because all supported CUDA platforms are little-endian, persisted context record data read with the new structure will have the correct value for `computeApiKind` and have a value of zero for `defaultStreamId`. The CUPTI client is responsible for versioning the persisted context data to recognize when the `defaultStreamId` field is valid.
- To ensure that metric values are calculated as accurately as possible, a new metric API is introduced. Function `cuptiMetricGetRequiredEventGroupSets` can be used to get the groups of events that should be collected at the same time.
- Execution overheads introduced by CUPTI have been dramatically decreased.
- The new activity buffer API introduced in CUDA Toolkit 5.5 is required. The legacy `cuptiActivityEnqueueBuffer` and `cuptiActivityDequeueBuffer` functions have been removed.

#### 1.1.26. Updates in CUDA 5.5

New Features

- Applications that use CUDA Dynamic Parallelism can be profiled using CUPTI. Device-side kernel launches are reported using a new activity kind.
- Device attributes such as power usage, clocks, thermals, etc. are reported via a new activity kind.
- A new activity buffer API uses callbacks to request and return buffers of activity records. The existing `cuptiActivityEnqueueBuffer` and `cuptiActivityDequeueBuffer` functions are still supported but are deprecated and will be removed in a future release.
- The Event API supports kernel replay so that any number of events can be collected during a single run of the application.
- A new metric API `cuptiMetricGetValue2` allows metric values to be calculated for any device, even if that device is not available on the system.
- CUDA peer-to-peer memory copies are reported explicitly via the activity API. In previous releases these memory copies were only partially reported.

### 1.2. Known Issues

The following are known issues with the current release.

- A security vulnerability issue required profiling tools to disable features using GPU performance counters for non-root or non-admin users when using a Windows 419.17 or Linux 418.43 or later driver. By default, NVIDIA drivers require elevated permissions to access GPU performance counters. On Tegra platforms, profile as root or using sudo. On other platforms, you can either start profiling as root or using sudo, or by enabling non-admin profiling. More details about the issue and the solutions can be found on the ERR_NVGPUCTRPERM web page.
  Note: CUPTI allows tracing features for non-root and non-admin users on desktop platforms only, Tegra platforms require root or sudo access.
- Profiling results might be inconsistent when auto boost is enabled. Profiler tries to disable auto boost by default. But it might fail to do so in some conditions and profiling will continue and results will be inconsistent. API `cuptiGetAutoBoostState()` can be used to query the auto boost state of the device. This API returns error `CUPTI_ERROR_NOT_SUPPORTED` on devices that don't support auto boost. Note that auto boost is supported only on certain Tesla devices with compute capability 3.0 and higher.
- CUPTI doesn't populate the activity structures which are deprecated, instead the newer version of the activity structure is filled with the information.
- Because of the low resolution of the timer on Windows, the start and end timestamps can be same for activities having short execution duration on Windows.
- The application which calls CUPTI APIs cannot be used with Nvidia tools like `nvprof`, `Nvidia Visual Profiler`, `Nsight Compute`, `Nsight Systems`, `Nvidia Nsight Visual Studio Edition`, `cuda-gdb` and `cuda-memcheck`.
- PCIE and NVLINK records are not captured when CUPTI is initialized lazily after the CUDA initialization.
- CUPTI fails to profile the OpenACC application when the OpenACC library linked with the application has missing definition of the OpenACC API routine/s. This is indicated by the error code `CUPTI_ERROR_OPENACC_UNDEFINED_ROUTINE`.
- OpenACC profiling might fail when OpenACC library is linked statically in the user application. This happens due to the missing definition of the OpenACC API routines needed for the OpenACC profiling, as compiler might ignore definitions for the functions not used in the application. This issue can be mitigated by linking the OpenACC library dynamically.
- Unified memory profiling is not supported on the ARM architecture.
- Profiling a C++ application which overloads the new operator at the global scope and uses any CUDA APIs like cudaMalloc() or cudaMallocManaged() inside the overloaded new operator will result in a hang.
- Devices with compute capability 6.0 and higher introduce a new feature, compute preemption, to give fair chance for all compute contexts while running long tasks. With compute preemption feature-
  - If multiple contexts are running in parallel it is possible that long kernels will get preempted.
  - Some kernels may get preempted occasionally due to timeslice expiry for the context.
  If kernel has been preempted, the time the kernel spends preempted is still counted towards kernel duration.
  Compute preemption can affect events and metrics collection. The following are known issues with the current release:
  - Events and metrics collection for a MPS client can result in higher counts than expected on devices with compute capability 7.0 and higher, since MPS client may get preempted due to termination of another MPS client.
  - Events warps_launched and sm_cta_launched and metric inst_per_warp might provide higher counts than expected on devices with compute capability 6.0 and higher. Metric unique_warps_launched can be used in place of warps_launched to get correct count of actual warps launched as it is not affected by compute preemption.

  To avoid compute preemption affecting profiler results try to isolate the context being profiled:

  - Run the application on secondary GPU where display is not connected.
  - On Linux if the application is running on the primary GPU where the display driver is connected then unload the display driver.
  - Run only one process that uses GPU at one time.
- Devices with compute capability 6.0 and higher support demand paging. When the kernel is scheduled for the first time, all the pages allocated using cudaMallocManaged and that are required for execution of the kernel are fetched in the global memory when GPU faults are generated. Profiler requires multiple passes to collect all the metrics required for kernel analysis. The kernel state needs to be saved and restored for each kernel replay pass. For devices with compute capability 6.0 and higher and platforms supporting Unified memory, in the first kernel iteration the GPU faults will be generated and all pages will be fetched in the global memory. Second iteration onwards GPU page faults will not occur. This will significantly affect the memory related events and timing. The time taken from trace will include the time required to fetch the pages but most of the metrics profiled in multiple iterations will not include time/cycles required to fetch the pages. This causes inconsistency in the profiler results.
- When profiling an application that uses CUDA Dynamic Parallelism (CDP) there are several limitations to the profiling tools.
  - CUDA Dynamic Parallelism (CDP) kernel launch tracing has a limitation for devices with compute capability 7.0 and higher. CUPTI traces all the host launched kernels until it encounters a host launched kernel which launches child kernels. Subsequent kernels are not traced.
  - CUPTI doesn't report CUDA API calls for device-launched kernels.
  - CUPTI doesn't report detailed event, metric, and source-level results for device-launched kernels. Event, metric, and source-level results collected for CPU-launched kernels will include event, metric, and source-level results for the entire call-tree of kernels launched from within that kernel.
- Compilation of samples autorange_profiling and userrange_profiling requires a host compiler which supports C++11 features. For some g++ compilers, it is required to use the flag -std=c++11 to turn on C++11 features.
- PC Sampling is not supported on Tegra platforms.
- As of CUDA 11.4 and R470 TRD1 driver release, CUPTI is supported in a vGPU environment which requires a vGPU license. If the license is not obtained after 20 minutes, the reported performance data including metrics from the GPU will be inaccurate. This is because of a feature in vGPU environment which reduces performance but retains functionality as specified here.
- CUPTI is not supported on NVIDIA Crypto Mining Processors (CMP). This is reported using the error code `CUPTI_ERROR_CMP_DEVICE_NOT_SUPPORTED`. For more information, please visit the web page.

#### 1.2.1. Profiling

The following are common known issues for both the event and metric APIs and the profiling APIs:

- Profiling may significantly change the overall performance characteristics of the application. Refer to the section CUPTI Overhead for more details.
- Profiling a kernel while other contexts are active on the same device (e.g. X server, or secondary CUDA or graphics application) can result in varying metric values for L2/FB (Device Memory) related metrics. Specifically, L2/FB traffic from non-profiled contexts cannot be excluded from the metric results. To completely avoid this issue, profile the application on a GPU without secondary contexts accessing the same device (e.g. no X server on Linux).
- Profiling is not supported for multidevice cooperative kernels, that is, kernels launched by using the API functions `cudaLaunchCooperativeKernelMultiDevice` or `cuLaunchCooperativeKernelMultiDevice`.
- Enabling certain events can cause GPU kernels to run longer than the driver's watchdog time-out limit. In these cases the driver will terminate the GPU kernel resulting in an application error and profiling data will not be available. Please disable the driver watchdog time out before profiling such long running CUDA kernels
  - On Linux, setting the X Config option Interactive to false is recommended.
  - For Windows, detailed information about TDR (Timeout Detection and Recovery) and how to disable it is available at https://docs.microsoft.com/en-us/windows-hardware/drivers/display/timeout-detection-and-recovery
- Profiling is not supported on the Windows Subsystem for Linux version 2 (WSL2).

##### 1.2.1.1. Event and Metric API

The following are known issues related to Event and Metric API:

- The CUPTI event APIs from the header `cupti_events.h` and metric APIs from the header `cupti_metrics.h` are not supported for the devices with compute capability 7.5 and higher. These are replaced by Profiling API and Perfworks metric API. Refer to the section Migration to the Profiling API.
- While collecting events in continuous mode, event reporting may be delayed i.e. event values may be returned by a later call to readEvent(s) API and the event values for the last readEvent(s) API may get lost.
- When profiling events, it is possible that the domain instance that gets profiled gives event value 0 due to absence of workload on the domain instance since CUPTI profiles one instance of the domain by default. To profile all instances of the domain, user can set event group attribute `CUPTI_EVENT_GROUP_ATTR_PROFILE_ALL_DOMAIN_INSTANCES` through API `cuptiEventGroupSetAttribute()`.
- Profiling results might be incorrect for CUDA applications compiled with nvcc version older than 9.0 for devices with compute capability 6.0 and 6.1. Profiling session will continue and CUPTI will notify it using error code `CUPTI_ERROR_CUDA_COMPILER_NOT_COMPATIBLE`. It is advised to recompile the application code with nvcc version 9.0 or later. Ignore this warning if code is already compiled with the recommended nvcc version.
- For some metrics, the required events can only be collected for a single CUDA context. For an application that uses multiple CUDA contexts, these metrics will only be collected for one of the contexts. The metrics that can be collected only for a single CUDA context are indicated in the metric reference tables.
- Some metric values are calculated assuming a kernel is large enough to occupy all device multiprocessors with approximately the same amount of work. If a kernel launch does not have this characteristic, then those metric values may not be accurate.
- Some events and metrics are not available on all devices. For list of metrics, you can refer to the metric reference tables.
- CUPTI can give out of memory error for event and metrics profiling, it could be due to large number of instructions in the kernel.
- Profiling is not supported for CUDA kernel nodes launched by a CUDA Graph.
- These APIs are not supported on below system configurations:
  - 64-bit ARM Server CPU architecture (arm64 SBSA).
  - Virtual GPUs (vGPU).

##### 1.2.1.2. Profiling and Perfworks Metric API

The following are known issues related to the Profiling and Perfworks Metric API:

- Profiling a kernel while any other GPU work is executing on the same MIG compute instance can result in varying metric values for all units. Care should be taken to serialize, or otherwise prevent concurrent CUDA launches within the target application to ensure those kernels do not influence each other. Be aware that GPU work issued through other APIs in the target process or workloads created by non-target processes running simultaneously in the same MIG compute instance will influence the collected metrics. Note that it is acceptable to run CUDA processes in other MIG compute instances as they will not influence the profiled MIG compute instance.
- For devices with compute capability 8.0, the NVLink topology information is available but NVLink performance metrics (`nvlrx__*` and `nvltx__*`) are not supported due to a potential application hang during data collection.
- Profiling is not supported under MPS (Multi-Process Service).
- For profiling the CUDA kernel nodes launched by a CUDA Graph, not all combinations of range profiling and replay modes are supported. User replay and application replay modes with auto range are not supported. In the user range mode, all the kernel nodes launched by the CUDA Graph will be profiled, user can't do the profiling for a range of kernels.
- Profiling kernels executed on a device that is part of an SLI group is not supported.
- Profiling is not supported for OptiX applications.
- Refer to the section for differences from event and metric APIs.

### 1.3. Support

Information on supported platforms and GPUs.

#### 1.3.1. Platform Support

Table 1. Platforms supported by CUPTI
Platform | Support
--- | ---
Windows | Yes
Windows Subsystem for Linux version 2 (WSL2) | Yes*
Linux (x86_64) | Yes
Linux (ppc64le) | Yes
Linux (aarch64 sbsa) | Yes*
Linux (x86_64) (Drive SDK) | Yes*
Linux (aarch64) | Yes*
QNX | Yes*
Mac OSX | No
Android | No

Tracing and profiling of 32-bit processes is not supported.

Event and Metric APIs are not supported on Linux (aarch64 sbsa) and WSL2 platforms.

The PC Sampling API is not supported on WSL2 and Tegra platforms - QNX, Linux (aarch64) and Linux (x86_64) (Drive SDK).

The Profiling API is not supported on WSL2 platform.

#### 1.3.2. GPU Support

Table 2. GPU architectures supported by different CUPTI APIs
CUPTI API | Supported GPU architectures | Notes
--- | --- | ---
Activity | Kepler and later GPU architectures, i.e. devices with compute capability 3.5 and higher |
Callback | Kepler and later GPU architectures, i.e. devices with compute capability 3.5 and higher |
Event | Kepler, Maxwell, Pascal, Volta | Not supported on Turing and later GPU architectures, i.e. devices with compute capability 7.5 and higher
Metric | Kepler, Maxwell, Pascal, Volta | Not supported on Turing and later GPU architectures, i.e. devices with compute capability 7.5 and higher
Profiling | Volta and later GPU architectures, i.e. devices with compute capability 7.0 and higher | Not supported on Kepler, Maxwell and Pascal GPUs
PC Sampling | Volta and later GPU architectures, i.e. devices with compute capability 7.0 and higher | Not supported on Kepler, Maxwell and Pascal GPUs
Checkpoint | Volta and later GPU architectures, i.e. devices with compute capability 7.0 and higher | Not supported on Kepler, Maxwell and Pascal GPUs