LLVM/OpenMP Runtimes¶

There are four distinct types of LLVM/OpenMP runtimes: the host runtime LLVM/OpenMP Host Runtime (libomp), the target offloading runtime LLVM/OpenMP Target Host Runtime (libomptarget), the target offloading plugin LLVM/OpenMP Target Host Runtime Plugins (libomptarget.rtl.XXXX), and finally the target device runtime LLVM/OpenMP Target Device Runtime (libomptarget-ARCH-SUBARCH.bc).

For general information on debugging OpenMP target offloading applications, see LIBOMPTARGET_INFO and Debugging

LLVM/OpenMP Host Runtime (`libomp`)¶

An early (2015) design document for the LLVM/OpenMP host runtime, aka. libomp.so, is available as a pdf.

Environment Variables¶

OMP_CANCELLATION¶

Enables cancellation of the innermost enclosing region of the type specified. If set to true, the effects of the cancel construct and of cancellation points are enabled and cancellation is activated. If set to false, cancellation is disabled and the cancel construct and cancellation points are effectively ignored.

Note

Internal barrier code will work differently depending on whether cancellation is enabled. Barrier code should repeatedly check the global flag to figure out if cancellation has been triggered. If a thread observes cancellation, it should leave the barrier prematurely with the return value 1 (and may wake up other threads). Otherwise, it should leave the barrier with the return value 0.

Enables (true) or disables (false) cancellation of the innermost enclosing region of the type specified.

Default: false

OMP_DISPLAY_ENV¶

Enables (true) or disables (false) the printing to stderr of the OpenMP version number and the values associated with the OpenMP environment variables.

Possible values are: true, false, or verbose.

Default: false

OMP_DEFAULT_DEVICE¶

Sets the device that will be used in a target region. The OpenMP routine omp_set_default_device or a device clause in a parallel pragma can override this variable. If no device with the specified device number exists, the code is executed on the host. If this environment variable is not set, device number 0 is used.

OMP_DYNAMIC¶

Enables (true) or disables (false) the dynamic adjustment of the number of threads.

Default: false

OMP_MAX_ACTIVE_LEVELS¶

The maximum number of levels of parallel nesting for the program.

Default: 1

OMP_NESTED¶

Warning

Deprecated. Please use OMP_MAX_ACTIVE_LEVELS to control nested parallelism

Enables (true) or disables (false) nested parallelism.

Default: false

OMP_NUM_THREADS¶

Sets the maximum number of threads to use for OpenMP parallel regions if no other value is specified in the application.

The value can be a single integer, in which case it specifies the number of threads for all parallel regions. The value can also be a comma-separated list of integers, in which case each integer specifies the number of threads for a parallel region at that particular nesting level.

The first position in the list represents the outer-most parallel nesting level, the second position represents the next-inner parallel nesting level, and so on. At any level, the integer can be left out of the list. If the first integer in a list is left out, it implies the normal default value for threads is used at the outer-most level. If the integer is left out of any other level, the number of threads for that level is inherited from the previous level.

Default: The number of processors visible to the operating system on which the program is executed.
Syntax: OMP_NUM_THREADS=value[,value]*
Example: OMP_NUM_THREADS=4,3

OMP_PLACES¶

Specifies an explicit ordered list of places, either as an abstract name describing a set of places or as an explicit list of places described by non-negative numbers. An exclusion operator, !, can also be used to exclude the number or place immediately following the operator.

For explicit lists, an ordered list of places is specified with each place represented as a set of non-negative numbers. The non-negative numbers represent operating system logical processor numbers and can be thought of as an OS affinity mask.

Individual places can be specified through two methods. Both the examples below represent the same place.

An explicit list of comma-separated non-negatives numbers Example: {0,2,4,6}
An interval with notation <lower-bound>:<length>[:<stride>]. Example: {0:4:2}. When <stride> is omitted, a unit stride is assumed. The interval notation represents this set of numbers:

<lower-bound>, <lower-bound> + <stride>, ..., <lower-bound> + (<length> - 1) * <stride>

A place list can also be specified using the same interval notation: {place}:<length>[:<stride>]. This represents the list of length <length> places determined by the following:

{place}, {place} + <stride>, ..., {place} + (<length>-1)*<stride>
Where given {place} and integer N, {place} + N = {place with every number offset by N}
Example: {0,3,6}:4:1 represents {0,3,6}, {1,4,7}, {2,5,8}, {3,6,9}

Examples of explicit lists: These all represent the same set of places

OMP_PLACES="{0,1,2,3},{4,5,6,7},{8,9,10,11},{12,13,14,15}"
OMP_PLACES="{0:4},{4:4},{8:4},{12:4}"
OMP_PLACES="{0:4}:4:4"

Note

When specifying a place using a set of numbers, if any number cannot be mapped to a processor on the target platform, then that number is ignored within the place, but the rest of the place is kept intact. If all numbers within a place are invalid, then the entire place is removed from the place list, but the rest of place list is kept intact.

The abstract names listed below are understood by the run-time environment:

threads: Each place corresponds to a single hardware thread.
cores: Each place corresponds to a single core (having one or more hardware threads).
sockets: Each place corresponds to a single socket (consisting of one or more cores).
numa_domains: Each place corresponds to a single NUMA domain (consisting of one or more cores).
ll_caches: Each place corresponds to a last-level cache (consisting of one or more cores).

The abstract name may be appended by a positive number in parentheses to denote the length of the place list to be created, that is abstract_name(num-places). If the optional number isn’t specified, then the runtime will use all available resources of type abstract_name. When requesting fewer places than available on the system, the first available resources as determined by abstract_name are used. When requesting more places than available on the system, only the available resources are used.

Examples of abstract names:

OMP_PLACES=threads
OMP_PLACES=threads(4)

OMP_PROC_BIND (Windows, Linux)¶

Sets the thread affinity policy to be used for parallel regions at the corresponding nested level. Enables (true) or disables (false) the binding of threads to processor contexts. If enabled, this is the same as specifying KMP_AFFINITY=scatter. If disabled, this is the same as specifying KMP_AFFINITY=none.

Acceptable values: true, false, or a comma separated list, each element of which is one of the following values: master, close, spread, or primary.

Default: false

Warning

master is deprecated. The semantics of master are the same as primary.

If set to false, the execution environment may move OpenMP threads between OpenMP places, thread affinity is disabled, and proc_bind clauses on parallel constructs are ignored. Otherwise, the execution environment should not move OpenMP threads between OpenMP places, thread affinity is enabled, and the initial thread is bound to the first place in the OpenMP place list.

If set to primary, all threads are bound to the same place as the primary thread.

If set to close, threads are bound to successive places, near where the primary thread is bound.

If set to spread, the primary thread’s partition is subdivided and threads are bound to single place successive sub-partitions.

Related environment variables: KMP_AFFINITY (overrides OMP_PROC_BIND).

OMP_SCHEDULE¶

Sets the run-time schedule type and an optional chunk size.

Default: static, no chunk size specified

Syntax: OMP_SCHEDULE="kind[,chunk_size]"

OMP_STACKSIZE¶

Sets the number of bytes to allocate for each OpenMP thread to use as the private stack for the thread. Recommended size is 16M.

Use the optional suffixes to specify byte units: B (bytes), K (Kilobytes), M (Megabytes), G (Gigabytes), or T (Terabytes) to specify the units. If you specify a value without a suffix, the byte unit is assumed to be K (Kilobytes).

This variable does not affect the native operating system threads created by the user program, or the thread executing the sequential part of an OpenMP program.

The kmp_{set,get}_stacksize_s() routines set/retrieve the value. The kmp_set_stacksize_s() routine must be called from sequential part, before first parallel region is created. Otherwise, calling kmp_set_stacksize_s() has no effect.

Default:

32-bit architecture: 2M
64-bit architecture: 4M

Related environment variables: KMP_STACKSIZE (overrides OMP_STACKSIZE).

Example: OMP_STACKSIZE=8M

OMP_THREAD_LIMIT¶

Limits the number of simultaneously-executing threads in an OpenMP program.

If this limit is reached and another native operating system thread encounters OpenMP API calls or constructs, the program can abort with an error message. If this limit is reached when an OpenMP parallel region begins, a one-time warning message might be generated indicating that the number of threads in the team was reduced, but the program will continue.

The omp_get_thread_limit() routine returns the value of the limit.

Default: No enforced limit

Related environment variable: KMP_ALL_THREADS (overrides OMP_THREAD_LIMIT).

OMP_WAIT_POLICY¶

Decides whether threads spin (active) or yield (passive) while they are waiting. OMP_WAIT_POLICY=active is an alias for KMP_LIBRARY=turnaround, and OMP_WAIT_POLICY=passive is an alias for KMP_LIBRARY=throughput.

Default: passive

Note

Although the default is passive, unless the user has explicitly set OMP_WAIT_POLICY, there is a small period of active spinning determined by KMP_BLOCKTIME.

KMP_AFFINITY (Windows, Linux)¶

Enables run-time library to bind threads to physical processing units.

You must set this environment variable before the first parallel region, or certain API calls including omp_get_max_threads(), omp_get_num_procs() and any affinity API calls.

Syntax: KMP_AFFINITY=[<modifier>,...]<type>[,<permute>][,<offset>]

modifiers are optional strings consisting of a keyword and possibly a specifier

respect (default) and norespect - determine whether to respect the original process affinity mask.
verbose and noverbose (default) - determine whether to display affinity information.
warnings (default) and nowarnings - determine whether to display warnings during affinity detection.
reset and noreset (default) - determine whether to reset primary thread’s affinity after outermost parallel region(s)
granularity=<specifier> - takes the following specifiers thread, core (default), tile, socket, die, group (Windows only). The granularity describes the lowest topology levels that OpenMP threads are allowed to float within a topology map. For example, if granularity=core, then the OpenMP threads will be allowed to move between logical processors within a single core. If granularity=thread, then the OpenMP threads will be restricted to a single logical processor.
proclist=[<proc_list>] - The proc_list is specified by

Value	Description
<proc_list> :=	<proc_id> \| { <id_list> }
<id_list> :=	<proc_id> \| <proc_id>,<id_list>

Where each proc_id represents an operating system logical processor ID. For example, proclist=[3,0,{1,2},{0,3}] with OMP_NUM_THREADS=4 would place thread 0 on OS logical processor 3, thread 1 on OS logical processor 0, thread 2 on both OS logical processors 1 & 2, and thread 3 on OS logical processors 0 & 3.

type is the thread affinity policy to choose. Valid choices are none, balanced, compact, scatter, explicit, disabled

type none (default) - Does not bind OpenMP threads to particular thread contexts; however, if the operating system supports affinity, the compiler still uses the OpenMP thread affinity interface to determine machine topology. Specify KMP_AFFINITY=verbose,none to list a machine topology map.
type compact - Specifying compact assigns the OpenMP thread <n>+1 to a free thread context as close as possible to the thread context where the <n> OpenMP thread was placed. For example, in a topology map, the nearer a node is to the root, the more significance the node has when sorting the threads.
type scatter - Specifying scatter distributes the threads as evenly as possible across the entire system. scatter is the opposite of compact; so the leaves of the node are most significant when sorting through the machine topology map.
type balanced - Places threads on separate cores until all cores have at least one thread, similar to the scatter type. However, when the runtime must use multiple hardware thread contexts on the same core, the balanced type ensures that the OpenMP thread numbers are close to each other, which scatter does not do. This affinity type is supported on the CPU only for single socket systems.
type explicit - Specifying explicit assigns OpenMP threads to a list of OS proc IDs that have been explicitly specified by using the proclist modifier, which is required for this affinity type.
type disabled - Specifying disabled completely disables the thread affinity interfaces. This forces the OpenMP run-time library to behave as if the affinity interface was not supported by the operating system. This includes the low-level API interfaces such as kmp_set_affinity and kmp_get_affinity, which have no effect and will return a nonzero error code.

For both compact and scatter, permute and offset are allowed; however, if you specify only one integer, the runtime interprets the value as a permute specifier. Both permute and offset default to 0.

The permute specifier controls which levels are most significant when sorting the machine topology map. A value for permute forces the mappings to make the specified number of most significant levels of the sort the least significant, and it inverts the order of significance. The root node of the tree is not considered a separate level for the sort operations.

The offset specifier indicates the starting position for thread assignment.

Default: noverbose,warnings,respect,granularity=core,none

Related environment variable: OMP_PROC_BIND (KMP_AFFINITY takes precedence)

Note

On Windows with multiple processor groups, the norespect affinity modifier is assumed when the process affinity mask equals a single processor group (which is default on Windows). Otherwise, the respect affinity modifier is used.

Note

On Windows with multiple processor groups, if the granularity is too coarse, it will be set to granularity=group. For example, if two processor groups exist across one socket, and granularity=socket the runtime will shift the granularity down to group since that is the largest granularity allowed by the OS.

KMP_HIDDEN_HELPER_AFFINITY (Windows, Linux)¶

Enables run-time library to bind hidden helper threads to physical processing units. This environment variable has the same syntax and semantics as KMP_AFFINIY but only applies to the hidden helper team.

You must set this environment variable before the first parallel region, or certain API calls including omp_get_max_threads(), omp_get_num_procs() and any affinity API calls.

Syntax: Same as KMP_AFFINITY

The following modifiers are ignored in KMP_HIDDEN_HELPER_AFFINITY and are only valid for KMP_AFFINITY: * respect and norespect * reset and noreset

KMP_ALL_THREADS¶

Limits the number of simultaneously-executing threads in an OpenMP program. If this limit is reached and another native operating system thread encounters OpenMP API calls or constructs, then the program may abort with an error message. If this limit is reached at the time an OpenMP parallel region begins, a one-time warning message may be generated indicating that the number of threads in the team was reduced, but the program will continue execution.

Default: No enforced limit.

Related environment variable: OMP_THREAD_LIMIT (KMP_ALL_THREADS takes precedence)

KMP_BLOCKTIME¶

Sets the time that a thread should wait, after completing the execution of a parallel region, before sleeping.

Use the optional suffixes: ms (milliseconds), or us (microseconds) to specify/change the units. Defaults units is milliseconds.

Specify infinite for an unlimited wait time.

Default: 200 milliseconds
Related Environment Variable: KMP_LIBRARY
Example: KMP_BLOCKTIME=1ms

KMP_CPUINFO_FILE¶

Specifies an alternate file name for a file containing the machine topology description. The file must be in the same format as /proc/cpuinfo.

Default: None

KMP_DETERMINISTIC_REDUCTION¶

Enables (true) or disables (false) the use of a specific ordering of the reduction operations for implementing the reduction clause for an OpenMP parallel region. This has the effect that, for a given number of threads, in a given parallel region, for a given data set and reduction operation, a floating point reduction done for an OpenMP reduction clause has a consistent floating point result from run to run, since round-off errors are identical.

Default: false

Example: KMP_DETERMINISTIC_REDUCTION=true

KMP_DYNAMIC_MODE¶

Selects the method used to determine the number of threads to use for a parallel region when OMP_DYNAMIC=true. Possible values: (load_balance | thread_limit), where,

load_balance: tries to avoid using more threads than available execution units on the machine;
thread_limit: tries to avoid using more threads than total execution units on the machine.

Default: load_balance (on all supported platforms)

KMP_HOT_TEAMS_MAX_LEVEL¶

Sets the maximum nested level to which teams of threads will be hot.

Note

A hot team is a team of threads optimized for faster reuse by subsequent parallel regions. In a hot team, threads are kept ready for execution of the next parallel region, in contrast to the cold team, which is freed after each parallel region, with its threads going into a common pool of threads.

For values of 2 and above, nested parallelism should be enabled.

Default: 1

KMP_HOT_TEAMS_MODE¶

Specifies the run-time behavior when the number of threads in a hot team is reduced. Possible values:

0 - Extra threads are freed and put into a common pool of threads.
1 - Extra threads are kept in the team in reserve, for faster reuse in subsequent parallel regions.

Default: 0

KMP_HW_SUBSET¶

Specifies the subset of available hardware resources for the hardware topology hierarchy. The subset is specified in terms of number of units per upper layer unit starting from top layer downwards. E.g. the number of sockets (top layer units), cores per socket, and the threads per core, to use with an OpenMP application, as an alternative to writing complicated explicit affinity settings or a limiting process affinity mask. You can also specify an offset value to set which resources to use. When available, you can specify attributes to select different subsets of resources.

An extended syntax is available when KMP_TOPOLOGY_METHOD=hwloc. Depending on what resources are detected, you may be able to specify additional resources, such as NUMA domains and groups of hardware resources that share certain cache levels.

Basic syntax: [:][num_units|*]ID[@offset][:attribute] [,[num_units|*]ID[@offset][:attribute]...]

An optional colon (:) can be specified at the beginning of the syntax to specify an explicit hardware subset. The default is an implicit hardware subset.

Supported unit IDs are not case-insensitive.

S - socket

num_units specifies the requested number of sockets.

D - die

num_units specifies the requested number of dies per socket.

C - core

num_units specifies the requested number of cores per die - if any - otherwise, per socket.

T - thread

num_units specifies the requested number of HW threads per core.

Note

num_units can be left out or explicitly specified as * instead of a positive integer meaning use all specified resources at that level. e.g., 1s,*c means use 1 socket and all the cores on that socket

offset - (Optional) The number of units to skip.

attribute - (Optional) An attribute differentiating resources at a particular level. The attributes available to users are:

Core type - On Intel architectures, this can be intel_atom or intel_core
Core efficiency - This is specified as effnum where num is a number from 0 to the number of core efficiencies detected in the machine topology minus one. E.g., eff0. The greater the efficiency number the more performant the core. There may be more core efficiencies than core types and can be viewed by setting KMP_AFFINITY=verbose

Note

The hardware cache can be specified as a unit, e.g. L2 for L2 cache, or LL for last level cache.

Extended syntax when KMP_TOPOLOGY_METHOD=hwloc:

Additional IDs can be specified if detected. For example:

N - numa num_units specifies the requested number of NUMA nodes per upper layer unit, e.g. per socket.

TI - tile num_units specifies the requested number of tiles to use per upper layer unit, e.g. per NUMA node.

When any numa or tile units are specified in KMP_HW_SUBSET and the hwloc topology method is available, the KMP_TOPOLOGY_METHOD will be automatically set to hwloc, so there is no need to set it explicitly.

For an explicit hardware subset, if one or more topology layers detected by the runtime are omitted from the subset, then those topology layers are ignored. Only explicitly specified topology layers are used in the subset.

For an implicit hardware subset, it is implied that the socket, core, and thread topology types should be included in the subset. Other topology layers are not implicitly included and are ignored if they are not specified in the subset. Because the socket, core and thread topology types are always included in implicit hardware subsets, when they are omitted, it is assumed that all available resources of that type should be used. Implicit hardware subsets are the default.

If you don’t specify one or more types of resource, such as socket or thread, all available resources of that type are used.

The run-time library prints a warning, and the setting of KMP_HW_SUBSET is ignored if:

a resource is specified, but detection of that resource is not supported by the chosen topology detection method and/or
a resource is specified twice. An exception to this condition is if attributes differentiate the resource.
attributes are used when not detected in the machine topology or conflict with each other.

This variable does not work if KMP_AFFINITY=disabled.

Default: If omitted, the default value is to use all the available hardware resources.

Implicit Hardware Subset Examples:

2s,4c,2t: Use the first 2 sockets (s0 and s1), the first 4 cores on each socket (c0 - c3), and 2 threads per core.
2s@2,4c@8,2t: Skip the first 2 sockets (s0 and s1) and use 2 sockets (s2-s3), skip the first 8 cores (c0-c7) and use 4 cores on each socket (c8-c11), and use 2 threads per core.
5C@1,3T: Use all available sockets, skip the first core and use 5 cores, and use 3 threads per core.
1T: Use all cores on all sockets, 1 thread per core.
1s, 1d, 1n, 1c, 1t: Use 1 socket, 1 die, 1 NUMA node, 1 core, 1 thread - use HW thread as a result.
4c:intel_atom,5c:intel_core: Use all available sockets and use 4 Intel Atom(R) processor cores and 5 Intel(R) Core(TM) processor cores per socket.
2c:eff0@1,3c:eff1: Use all available sockets, skip the first core with efficiency 0 and use the next 2 cores with efficiency 0 and 3 cores with efficiency 1 per socket.
1s, 1c, 1t: Use 1 socket, 1 core, 1 thread. This may result in using single thread on a 3-layer topology architecture, or multiple threads on 4-layer or 5-layer architecture. Result may even be different on the same architecture, depending on KMP_TOPOLOGY_METHOD specified, as hwloc can often detect more topology layers than the default method used by the OpenMP run-time library.
*c:eff1@3: Use all available sockets, skip the first three cores of efficiency 1, and then use the rest of the available cores of efficiency 1.

Explicit Hardware Subset Examples:

:2s,6t Use exactly the first two sockets and 6 threads per socket.
:1t@7 Skip the first 7 threads (t0-t6) and use exactly one thread (t7).
:5c,1t Use exactly the first 5 cores (c0-c4) and the first thread on each core.

To see the result of the setting, you can specify verbose modifier in KMP_AFFINITY environment variable. The OpenMP run-time library will output to stderr the information about the discovered hardware topology before and after the KMP_HW_SUBSET setting was applied.

KMP_INHERIT_FP_CONTROL¶

Enables (true) or disables (false) the copying of the floating-point control settings of the primary thread to the floating-point control settings of the OpenMP worker threads at the start of each parallel region.

Default: true

KMP_LIBRARY¶

Selects the OpenMP run-time library execution mode. The values for this variable are serial, turnaround, or throughput.

Default: throughput

Related environment variable: KMP_BLOCKTIME and OMP_WAIT_POLICY

KMP_SETTINGS¶

Enables (true) or disables (false) the printing of OpenMP run-time library environment variables during program execution. Two lists of variables are printed: user-defined environment variables settings and effective values of variables used by OpenMP run-time library.

Default: false

KMP_STACKSIZE¶

Sets the number of bytes to allocate for each OpenMP thread to use as its private stack.

Recommended size is 16M.

Related environment variable: KMP_STACKSIZE overrides GOMP_STACKSIZE, which overrides OMP_STACKSIZE.

Default:

32-bit architectures: 2M
64-bit architectures: 4M

KMP_TOPOLOGY_METHOD¶

Forces OpenMP to use a particular machine topology modeling method.

Possible values are:

all - Let OpenMP choose which topology method is most appropriate based on the platform and possibly other environment variable settings.
cpuid_leaf31 (x86 only) - Decodes the APIC identifiers as specified by leaf 31 of the cpuid instruction. The runtime will produce an error if the machine does not support leaf 31.
cpuid_leaf11 (x86 only) - Decodes the APIC identifiers as specified by leaf 11 of the cpuid instruction. The runtime will produce an error if the machine does not support leaf 11.
cpuid_leaf4 (x86 only) - Decodes the APIC identifiers as specified in leaf 4 of the cpuid instruction. The runtime will produce an error if the machine does not support leaf 4.
cpuinfo - If KMP_CPUINFO_FILE is not specified, forces OpenMP to parse /proc/cpuinfo to determine the topology (Linux only). If KMP_CPUINFO_FILE is specified as described above, uses it (Windows or Linux).
group - Models the machine as a 2-level map, with level 0 specifying the different processors in a group, and level 1 specifying the different groups (Windows 64-bit only).

Note

Support for group is now deprecated and will be removed in a future release. Use all instead.

flat - Models the machine as a flat (linear) list of processors.
hwloc - Models the machine as the Portable Hardware Locality (hwloc) library does. This model is the most detailed and includes, but is not limited to: numa domains, packages, cores, hardware threads, caches, and Windows processor groups. This method is only available if you have configured libomp to use hwloc during CMake configuration.

Default: all

KMP_VERSION¶

Enables (true) or disables (false) the printing of OpenMP run-time library version information during program execution.

Default: false

KMP_WARNINGS¶

Enables (true) or disables (false) displaying warnings from the OpenMP run-time library during program execution.

Default: true

LLVM/OpenMP Target Host Runtime (`libomptarget`)¶

Environment Variables¶

libomptarget uses environment variables to control different features of the library at runtime. This allows the user to obtain useful runtime information as well as enable or disable certain features. A full list of supported environment variables is defined below.

LIBOMPTARGET_DEBUG=<Num>

LIBOMPTARGET_PROFILE=<Filename>

LIBOMPTARGET_PROFILE_GRANULARITY=<Num> (default 500, in us)

LIBOMPTARGET_MEMORY_MANAGER_THRESHOLD=<Num>

LIBOMPTARGET_INFO=<Num>

LIBOMPTARGET_HEAP_SIZE=<Num>

LIBOMPTARGET_STACK_SIZE=<Num>

LIBOMPTARGET_SHARED_MEMORY_SIZE=<Num>

LIBOMPTARGET_MAP_FORCE_ATOMIC=[TRUE/FALSE] (default TRUE)

LIBOMPTARGET_JIT_OPT_LEVEL={0,1,2,3} (default 3)

LIBOMPTARGET_JIT_SKIP_OPT=[TRUE/FALSE] (default FALSE)

LIBOMPTARGET_JIT_REPLACEMENT_OBJECT=<in:Filename> (object file)

LIBOMPTARGET_JIT_REPLACEMENT_MODULE=<in:Filename> (LLVM-IR file)

LIBOMPTARGET_JIT_PRE_OPT_IR_MODULE=<out:Filename> (LLVM-IR file)

LIBOMPTARGET_JIT_POST_OPT_IR_MODULE=<out:Filename> (LLVM-IR file)

LIBOMPTARGET_MIN_THREADS_FOR_LOW_TRIP_COUNT=<Num> (default: 32)

LIBOMPTARGET_REUSE_BLOCKS_FOR_HIGH_TRIP_COUNT=[TRUE/FALSE] (default TRUE)

OFFLOAD_TRACK_ALLOCATION_TRACES=[TRUE/FALSE] (default FALSE)

OFFLOAD_TRACK_NUM_KERNEL_LAUNCH_TRACES=<Num> (default 0)

LIBOMPTARGET_DEBUG¶

LIBOMPTARGET_DEBUG controls whether or not debugging information will be displayed. This feature is only available if libomptarget was built with -DOMPTARGET_DEBUG. The debugging output provided is intended for use by libomptarget developers. More user-friendly output is presented when using LIBOMPTARGET_INFO.

LIBOMPTARGET_PROFILE¶

LIBOMPTARGET_PROFILE allows libomptarget to generate time profile output similar to Clang’s -ftime-trace option. This generates a JSON file based on Chrome Tracing that can be viewed with chrome://tracing or the Speedscope App. The output will be saved to the filename specified by the environment variable. For multi-threaded applications, profiling in libomp is also needed. Setting the CMake option OPENMP_ENABLE_LIBOMP_PROFILING=ON to enable the feature. This feature depends on the LLVM Support Library for time trace output. Note that this will turn libomp into a C++ library.

LIBOMPTARGET_PROFILE_GRANULARITY¶

LIBOMPTARGET_PROFILE_GRANULARITY allows to change the time profile granularity measured in us. Default is 500 (us).

LIBOMPTARGET_MEMORY_MANAGER_THRESHOLD¶

LIBOMPTARGET_MEMORY_MANAGER_THRESHOLD sets the threshold size for which the libomptarget memory manager will handle the allocation. Any allocations larger than this threshold will not use the memory manager and be freed after the device kernel exits. The default threshold value is 8KB. If LIBOMPTARGET_MEMORY_MANAGER_THRESHOLD is set to 0 the memory manager will be completely disabled.

LIBOMPTARGET_INFO¶

LIBOMPTARGET_INFO allows the user to request different types of runtime information from libomptarget. LIBOMPTARGET_INFO uses a 32-bit field to enable or disable different types of information. This includes information about data-mappings and kernel execution. It is recommended to build your application with debugging information enabled, this will enable filenames and variable declarations in the information messages. OpenMP Debugging information is enabled at any level of debugging so a full debug runtime is not required. For minimal debugging information compile with -gline-tables-only, or compile with -g for full debug information. A full list of flags supported by LIBOMPTARGET_INFO is given below.

Print all data arguments upon entering an OpenMP device kernel: 0x01

Indicate when a mapped address already exists in the device mapping table: 0x02

Dump the contents of the device pointer map at kernel exit: 0x04

Indicate when an entry is changed in the device mapping table: 0x08

Print OpenMP kernel information from device plugins: 0x10

Indicate when data is copied to and from the device: 0x20

Any combination of these flags can be used by setting the appropriate bits. For example, to enable printing all data active in an OpenMP target region along with CUDA information, run the following bash command.

$ env LIBOMPTARGET_INFO=$((0x1 | 0x10)) ./your-application

Or, to enable every flag run with every bit set.

$ env LIBOMPTARGET_INFO=-1 ./your-application

For example, given a small application implementing the ZAXPY BLAS routine, Libomptarget can provide useful information about data mappings and thread usages.

#include <complex>

using complex = std::complex<double>;

void zaxpy(complex *X, complex *Y, complex D, std::size_t N) {
#pragma omp target teams distribute parallel for
  for (std::size_t i = 0; i < N; ++i)
    Y[i] = D * X[i] + Y[i];
}

int main() {
  const std::size_t N = 1024;
  complex X[N], Y[N], D;
#pragma omp target data map(to:X[0 : N]) map(tofrom:Y[0 : N])
  zaxpy(X, Y, D, N);
}

Compiling this code targeting nvptx64 with all information enabled will provide the following output from the runtime library.

$ clang++ -fopenmp -fopenmp-targets=nvptx64 -O3 -gline-tables-only zaxpy.cpp -o zaxpy
$ env LIBOMPTARGET_INFO=-1 ./zaxpy

Info: Entering OpenMP data region at zaxpy.cpp:14:1 with 2 arguments:
Info: to(X[0:N])[16384]
Info: tofrom(Y[0:N])[16384]
Info: Creating new map entry with HstPtrBegin=0x00007fff0d259a40,
      TgtPtrBegin=0x00007fdba5800000, Size=16384, RefCount=1, Name=X[0:N]
Info: Copying data from host to device, HstPtr=0x00007fff0d259a40,
      TgtPtr=0x00007fdba5800000, Size=16384, Name=X[0:N]
Info: Creating new map entry with HstPtrBegin=0x00007fff0d255a40,
      TgtPtrBegin=0x00007fdba5804000, Size=16384, RefCount=1, Name=Y[0:N]
Info: Copying data from host to device, HstPtr=0x00007fff0d255a40,
      TgtPtr=0x00007fdba5804000, Size=16384, Name=Y[0:N]
Info: OpenMP Host-Device pointer mappings after block at zaxpy.cpp:14:1:
Info: Host Ptr           Target Ptr         Size (B) RefCount Declaration
Info: 0x00007fff0d255a40 0x00007fdba5804000 16384    1        Y[0:N] at zaxpy.cpp:13:17
Info: 0x00007fff0d259a40 0x00007fdba5800000 16384    1        X[0:N] at zaxpy.cpp:13:11
Info: Entering OpenMP kernel at zaxpy.cpp:6:1 with 4 arguments:
Info: firstprivate(N)[8] (implicit)
Info: use_address(Y)[0] (implicit)
Info: tofrom(D)[16] (implicit)
Info: use_address(X)[0] (implicit)
Info: Mapping exists (implicit) with HstPtrBegin=0x00007fff0d255a40,
      TgtPtrBegin=0x00007fdba5804000, Size=0, RefCount=2 (incremented), Name=Y
Info: Creating new map entry with HstPtrBegin=0x00007fff0d2559f0,
      TgtPtrBegin=0x00007fdba5808000, Size=16, RefCount=1, Name=D
Info: Copying data from host to device, HstPtr=0x00007fff0d2559f0,
      TgtPtr=0x00007fdba5808000, Size=16, Name=D
Info: Mapping exists (implicit) with HstPtrBegin=0x00007fff0d259a40,
      TgtPtrBegin=0x00007fdba5800000, Size=0, RefCount=2 (incremented), Name=X
Info: Mapping exists with HstPtrBegin=0x00007fff0d255a40,
      TgtPtrBegin=0x00007fdba5804000, Size=0, RefCount=2 (update suppressed)
Info: Mapping exists with HstPtrBegin=0x00007fff0d2559f0,
      TgtPtrBegin=0x00007fdba5808000, Size=16, RefCount=1 (update suppressed)
Info: Mapping exists with HstPtrBegin=0x00007fff0d259a40,
      TgtPtrBegin=0x00007fdba5800000, Size=0, RefCount=2 (update suppressed)
Info: Launching kernel __omp_offloading_10305_c08c86__Z5zaxpyPSt7complexIdES1_S0_m_l6
      with 8 blocks and 128 threads in SPMD mode
Info: Mapping exists with HstPtrBegin=0x00007fff0d259a40,
      TgtPtrBegin=0x00007fdba5800000, Size=0, RefCount=1 (decremented)
Info: Mapping exists with HstPtrBegin=0x00007fff0d2559f0,
      TgtPtrBegin=0x00007fdba5808000, Size=16, RefCount=1 (deferred final decrement)
Info: Copying data from device to host, TgtPtr=0x00007fdba5808000,
      HstPtr=0x00007fff0d2559f0, Size=16, Name=D
Info: Mapping exists with HstPtrBegin=0x00007fff0d255a40,
      TgtPtrBegin=0x00007fdba5804000, Size=0, RefCount=1 (decremented)
Info: Removing map entry with HstPtrBegin=0x00007fff0d2559f0,
      TgtPtrBegin=0x00007fdba5808000, Size=16, Name=D
Info: OpenMP Host-Device pointer mappings after block at zaxpy.cpp:6:1:
Info: Host Ptr           Target Ptr         Size (B) RefCount Declaration
Info: 0x00007fff0d255a40 0x00007fdba5804000 16384    1        Y[0:N] at zaxpy.cpp:13:17
Info: 0x00007fff0d259a40 0x00007fdba5800000 16384    1        X[0:N] at zaxpy.cpp:13:11
Info: Exiting OpenMP data region at zaxpy.cpp:14:1 with 2 arguments:
Info: to(X[0:N])[16384]
Info: tofrom(Y[0:N])[16384]
Info: Mapping exists with HstPtrBegin=0x00007fff0d255a40,
      TgtPtrBegin=0x00007fdba5804000, Size=16384, RefCount=1 (deferred final decrement)
Info: Copying data from device to host, TgtPtr=0x00007fdba5804000,
      HstPtr=0x00007fff0d255a40, Size=16384, Name=Y[0:N]
Info: Mapping exists with HstPtrBegin=0x00007fff0d259a40,
      TgtPtrBegin=0x00007fdba5800000, Size=16384, RefCount=1 (deferred final decrement)
Info: Removing map entry with HstPtrBegin=0x00007fff0d255a40,
      TgtPtrBegin=0x00007fdba5804000, Size=16384, Name=Y[0:N]
Info: Removing map entry with HstPtrBegin=0x00007fff0d259a40,
      TgtPtrBegin=0x00007fdba5800000, Size=16384, Name=X[0:N]

From this information, we can see the OpenMP kernel being launched on the CUDA device with enough threads and blocks for all 1024 iterations of the loop in simplified SPMD Mode. The information from the OpenMP data region shows the two arrays X and Y being copied from the host to the device. This creates an entry in the host-device mapping table associating the host pointers to the newly created device data. The data mappings in the OpenMP device kernel show the default mappings being used for all the variables used implicitly on the device. Because X and Y are already mapped in the device’s table, no new entries are created. Additionally, the default mapping shows that D will be copied back from the device once the OpenMP device kernel region ends even though it isn’t written to. Finally, at the end of the OpenMP data region the entries for X and Y are removed from the table.

The information level can be controlled at runtime using an internal libomptarget library call __tgt_set_info_flag. This allows for different levels of information to be enabled or disabled for certain regions of code. Using this requires declaring the function signature as an external function so it can be linked with the runtime library.

extern "C" void __tgt_set_info_flag(uint32_t);

extern foo();

int main() {
  __tgt_set_info_flag(0x10);
#pragma omp target
  foo();
}

Errors:¶

libomptarget provides error messages when the program fails inside the OpenMP target region. Common causes of failure could be an invalid pointer access, running out of device memory, or trying to offload when the device is busy. If the application was built with debugging symbols the error messages will additionally provide the source location of the OpenMP target region.

For example, consider the following code that implements a simple parallel reduction on the GPU. This code has a bug that causes it to fail in the offloading region.

#include <cstdio>

double sum(double *A, std::size_t N) {
  double sum = 0.0;
#pragma omp target teams distribute parallel for reduction(+:sum)
  for (int i = 0; i < N; ++i)
    sum += A[i];

  return sum;
}

int main() {
  const int N = 1024;
  double A[N];
  sum(A, N);
}

If this code is compiled and run, there will be an error message indicating what is going wrong.

$ clang++ -fopenmp -fopenmp-targets=nvptx64 -O3 -gline-tables-only sum.cpp -o sum
$ ./sum

CUDA error: an illegal memory access was encountered
Libomptarget error: Copying data from device failed.
Libomptarget error: Call to targetDataEnd failed, abort target.
Libomptarget error: Failed to process data after launching the kernel.
Libomptarget error: Consult https://openmp.llvm.org/design/Runtimes.html for debugging options.
sum.cpp:5:1: Libomptarget error 1: failure of target construct while offloading is mandatory

This shows that there is an illegal memory access occurring inside the OpenMP target region once execution has moved to the CUDA device, suggesting a segmentation fault. This then causes a chain reaction of failures in libomptarget. Another message suggests using the LIBOMPTARGET_INFO environment variable as described in Environment Variables. If we do this it will print the sate of the host-target pointer mappings at the time of failure.

$ clang++ -fopenmp -fopenmp-targets=nvptx64 -O3 -gline-tables-only sum.cpp -o sum
$ env LIBOMPTARGET_INFO=4 ./sum

info: OpenMP Host-Device pointer mappings after block at sum.cpp:5:1:
info: Host Ptr           Target Ptr         Size (B) RefCount Declaration
info: 0x00007ffc058280f8 0x00007f4186600000 8        1        sum at sum.cpp:4:10

This tells us that the only data mapped between the host and the device is the sum variable that will be copied back from the device once the reduction has ended. There is no entry mapping the host array A to the device. In this situation, the compiler cannot determine the size of the array at compile time so it will simply assume that the pointer is mapped on the device already by default. The solution is to add an explicit map clause in the target region.

double sum(double *A, std::size_t N) {
  double sum = 0.0;
#pragma omp target teams distribute parallel for reduction(+:sum) map(to:A[0 : N])
  for (int i = 0; i < N; ++i)
    sum += A[i];

  return sum;
}

LIBOMPTARGET_STACK_SIZE¶

This environment variable sets the stack size in bytes for the AMDGPU and CUDA plugins. This can be used to increase or decrease the standard amount of memory reserved for each thread’s stack.

LIBOMPTARGET_HEAP_SIZE¶

This environment variable sets the amount of memory in bytes that can be allocated using malloc and free for the CUDA plugin. This is necessary for some applications that allocate too much memory either through the user or globalization.

LIBOMPTARGET_SHARED_MEMORY_SIZE¶

This environment variable sets the amount of dynamic shared memory in bytes used by the kernel once it is launched. A pointer to the dynamic memory buffer can be accessed using the llvm_omp_target_dynamic_shared_alloc function. An example is shown in Dynamic Shared Memory.

LIBOMPTARGET_MAP_FORCE_ATOMIC¶

The OpenMP standard guarantees that map clauses are atomic. However, the this can have a drastic performance impact. Users that do not require atomic map clauses can disable them to potentially recover lost performance. As a consequence, users have to guarantee themselves that no two map clauses will concurrently map the same memory. If the memory is already mapped and the map clauses will only modify the reference counter from a non-zero count to another non-zero count, concurrent map clauses are supported regardless of this option. To disable forced atomic map clauses use “false”/”FALSE” as the value of the LIBOMPTARGET_MAP_FORCE_ATOMIC environment variable. The default behavior of LLVM 14 is to force atomic maps clauses, prior versions of LLVM did not.

LIBOMPTARGET_JIT_OPT_LEVEL¶

This environment variable can be used to change the optimization pipeline used to optimize the embedded device code as part of the device JIT. The value is corresponds to the -O{0,1,2,3} command line argument passed to clang.

LIBOMPTARGET_JIT_SKIP_OPT¶

This environment variable can be used to skip the optimization pipeline during JIT compilation. If set, the image will only be passed through the backend. The backend is invoked with the LIBOMPTARGET_JIT_OPT_LEVEL flag.

LIBOMPTARGET_JIT_REPLACEMENT_OBJECT¶

This environment variable can be used to replace the embedded device code before the device JIT finishes compilation for the target. The value is expected to be a filename to an object file, thus containing the output of the assembler in object format for the respective target. The JIT optimization pipeline and backend are skipped and only target specific post-processing is performed on the object file before it is loaded onto the device.

LIBOMPTARGET_JIT_REPLACEMENT_MODULE¶

This environment variable can be used to replace the embedded device code before the device JIT finishes compilation for the target. The value is expected to be a filename to an LLVM-IR file, thus containing an LLVM-IR module for the respective target. To obtain a device code image compatible with the embedded one it is recommended to extract the embedded one either before or after IR optimization. This can be done at compile time, after compile time via llvm tools (llvm-objdump), or, simply, by setting the LIBOMPTARGET_JIT_PRE_OPT_IR_MODULE or LIBOMPTARGET_JIT_POST_OPT_IR_MODULE environment variables.

LIBOMPTARGET_JIT_PRE_OPT_IR_MODULE¶

This environment variable can be used to extract the embedded device code before the device JIT runs additional IR optimizations on it (see LIBOMPTARGET_JIT_OPT_LEVEL). The value is expected to be a filename into which the LLVM-IR module is written. The module can be the analyzed, and transformed and loaded back into the JIT pipeline via LIBOMPTARGET_JIT_REPLACEMENT_MODULE.

LIBOMPTARGET_JIT_POST_OPT_IR_MODULE¶

This environment variable can be used to extract the embedded device code after the device JIT runs additional IR optimizations on it (see LIBOMPTARGET_JIT_OPT_LEVEL). The value is expected to be a filename into which the LLVM-IR module is written. The module can be the analyzed, and transformed and loaded back into the JIT pipeline via LIBOMPTARGET_JIT_REPLACEMENT_MODULE.

LIBOMPTARGET_MIN_THREADS_FOR_LOW_TRIP_COUNT¶

This environment variable defines a lower bound for the number of threads if a combined kernel, e.g., target teams distribute parallel for, has insufficient parallelism. Especially if the trip count of the loops is lower than the number of threads possible times the number of teams (aka. blocks) the device prefers (see also LIBOMPTARGET_AMDGPU_TEAMS_PER_CU), we will reduce the thread count to increase outer (team/block) parallelism. The thread count will never be reduced below the value passed for this environment variable though.

LIBOMPTARGET_REUSE_BLOCKS_FOR_HIGH_TRIP_COUNT¶

This environment variable can be used to control how the OpenMP runtime assigns blocks to loops with high trip counts. By default we reuse existing blocks rather than spawning new blocks.

OFFLOAD_TRACK_ALLOCATION_TRACES¶

This environment variable determines if the stack traces of allocations and deallocations are tracked to aid in error reporting, e.g., in case of double-free.

OFFLOAD_TRACK_KERNEL_LAUNCH_TRACES¶

This environment variable determines how manytstack traces of kernel launches are tracked to aid in error reporting, e.g., what asynchronous kernel failed.

LLVM/OpenMP Target Host Runtime Plugins (`libomptarget.rtl.XXXX`)¶

The LLVM/OpenMP target host runtime plugins were recently re-implemented, temporarily renamed as the NextGen plugins, and set as the default and only plugins’ implementation. Currently, these plugins have support for the NVIDIA and AMDGPU devices as well as the GenericELF64bit host-simulated device.

The source code of the common infrastructure and the vendor-specific plugins is in the openmp/libomptarget/nextgen-plugins directory in the LLVM project repository. The plugin infrastructure aims at unifying the plugin code and logic into a generic interface using object-oriented C++. There is a plugin interface composed by multiple generic C++ classes which implement the common logic that every vendor-specific plugin should provide. In turn, the specific plugins inherit from those generic classes and implement the required functions that depend on the specific vendor API. As an example, some generic classes that the plugin interface define are for representing a device, a device image, an efficient resource manager, etc.

With this common plugin infrastructure, several tasks have been simplified: adding a new vendor-specific plugin, adding generic features or optimizations to all plugins, debugging plugins, etc.

Environment Variables¶

There are several environment variables to change the behavior of the plugins:

LIBOMPTARGET_SHARED_MEMORY_SIZE
LIBOMPTARGET_STACK_SIZE
LIBOMPTARGET_HEAP_SIZE
LIBOMPTARGET_NUM_INITIAL_STREAMS
LIBOMPTARGET_NUM_INITIAL_EVENTS
LIBOMPTARGET_LOCK_MAPPED_HOST_BUFFERS
LIBOMPTARGET_AMDGPU_NUM_HSA_QUEUES
LIBOMPTARGET_AMDGPU_HSA_QUEUE_SIZE
LIBOMPTARGET_AMDGPU_HSA_QUEUE_BUSY_TRACKING
LIBOMPTARGET_AMDGPU_TEAMS_PER_CU
LIBOMPTARGET_AMDGPU_MAX_ASYNC_COPY_BYTES
LIBOMPTARGET_AMDGPU_NUM_INITIAL_HSA_SIGNALS
LIBOMPTARGET_AMDGPU_STREAM_BUSYWAIT

The environment variables LIBOMPTARGET_SHARED_MEMORY_SIZE, LIBOMPTARGET_STACK_SIZE and LIBOMPTARGET_HEAP_SIZE are described in Environment Variables.

LIBOMPTARGET_NUM_INITIAL_STREAMS¶

This environment variable sets the number of pre-created streams in the plugin (if supported) at initialization. More streams will be created dynamically throughout the execution if needed. A stream is a queue of asynchronous operations (e.g., kernel launches and memory copies) that are executed sequentially. Parallelism is achieved by featuring multiple streams. The libomptarget leverages streams to exploit parallelism between plugin operations. The default value is 1, more streams are created as needed.

LIBOMPTARGET_NUM_INITIAL_EVENTS¶

This environment variable sets the number of pre-created events in the plugin (if supported) at initialization. More events will be created dynamically throughout the execution if needed. An event is used to synchronize a stream with another efficiently. The default value is 1, more events are created as needed.

LIBOMPTARGET_LOCK_MAPPED_HOST_BUFFERS¶

This environment variable indicates whether the host buffers mapped by the user should be automatically locked/pinned by the plugin. Pinned host buffers allow true asynchronous copies between the host and devices. Enabling this feature can increase the performance of applications that are intensive in host-device memory transfers. The default value is false.

LIBOMPTARGET_AMDGPU_NUM_HSA_QUEUES¶

This environment variable controls the number of HSA queues per device in the AMDGPU plugin. An HSA queue is a runtime-allocated resource that contains an AQL (Architected Queuing Language) packet buffer and is associated with an AQL packet processor. HSA queues are used for inserting kernel packets to launching kernel executions. A high number of HSA queues may degrade the performance. The default value is 4.

LIBOMPTARGET_AMDGPU_HSA_QUEUE_SIZE¶

This environment variable controls the size of each HSA queue in the AMDGPU plugin. The size is the number of AQL packets an HSA queue is expected to hold. It is also the number of AQL packets that can be pushed into each queue without waiting the driver to process them. The default value is 512.

LIBOMPTARGET_AMDGPU_HSA_QUEUE_BUSY_TRACKING¶

This environment variable controls if idle HSA queues will be preferentially assigned to streams, for example when they are requested for a kernel launch. Should all queues be considered busy, a new queue is initialized and returned, until we reach the set maximum. Otherwise, we will select the least utilized queue. If this is disabled, each time a stream is requested a new HSA queue will be initialized, regardless of their utilization. Additionally, queues will be selected using round robin selection. The default value is true.

LIBOMPTARGET_AMDGPU_TEAMS_PER_CU¶

This environment variable controls the default number of teams relative to the number of compute units (CUs) of the AMDGPU device. The default number of teams is #default_teams = #teams_per_CU * #CUs. The default value of teams per CU is 4.

LIBOMPTARGET_AMDGPU_MAX_ASYNC_COPY_BYTES¶

This environment variable specifies the maximum size in bytes where the memory copies are asynchronous operations in the AMDGPU plugin. Up to this transfer size, the memory copies are asynchronous operations pushed to the corresponding stream. For larger transfers, they are synchronous transfers. Memory copies involving already locked/pinned host buffers are always asynchronous. The default value is 1*1024*1024 bytes (1 MB).

LIBOMPTARGET_AMDGPU_NUM_INITIAL_HSA_SIGNALS¶

This environment variable controls the initial number of HSA signals per device in the AMDGPU plugin. There is one resource manager of signals per device managing several pre-created signals. These signals are mainly used by AMDGPU streams. More HSA signals will be created dynamically throughout the execution if needed. The default value is 64.

LIBOMPTARGET_AMDGPU_STREAM_BUSYWAIT¶

This environment variable controls the timeout hint in microseconds for the HSA wait state within the AMDGPU plugin. For the duration of this value the HSA runtime may busy wait. This can reduce overall latency. The default value is 2000000.

Remote Offloading Plugin:¶

The remote offloading plugin permits the execution of OpenMP target regions on devices in remote hosts in addition to the devices connected to the local host. All target devices on the remote host will be exposed to the application as if they were local devices, that is, the remote host CPU or its GPUs can be offloaded to with the appropriate device number. If the server is running on the same host, each device may be identified twice: once through the device plugins and once through the device plugins that the server application has access to.

This plugin consists of libomptarget.rtl.rpc.so and openmp-offloading-server which should be running on the (remote) host. The server application does not have to be running on a remote host, and can instead be used on the same host in order to debug memory mapping during offloading. These are implemented via gRPC/protobuf so these libraries are required to build and use this plugin. The server must also have access to the necessary target-specific plugins in order to perform the offloading.

Due to the experimental nature of this plugin, the CMake variable LIBOMPTARGET_ENABLE_EXPERIMENTAL_REMOTE_PLUGIN must be set in order to build this plugin. For example, the rpc plugin is not designed to be thread-safe, the server cannot concurrently handle offloading from multiple applications at once (it is synchronous) and will terminate after a single execution. Note that openmp-offloading-server is unable to remote offload onto a remote host itself and will error out if this is attempted.

Remote offloading is configured via environment variables at runtime of the OpenMP application:

LIBOMPTARGET_RPC_ADDRESS=<Address>:<Port>
LIBOMPTARGET_RPC_ALLOCATOR_MAX=<NumBytes>
LIBOMPTARGET_BLOCK_SIZE=<NumBytes>
LIBOMPTARGET_RPC_LATENCY=<Seconds>

LIBOMPTARGET_RPC_ADDRESS¶

The address and port at which the server is running. This needs to be set for the server and the application, the default is 0.0.0.0:50051. A single OpenMP executable can offload onto multiple remote hosts by setting this to comma-separated values of the addresses.

LIBOMPTARGET_RPC_ALLOCATOR_MAX¶

After allocating this size, the protobuf allocator will clear. This can be set for both endpoints.

LIBOMPTARGET_BLOCK_SIZE¶

This is the maximum size of a single message while streaming data transfers between the two endpoints and can be set for both endpoints.

LIBOMPTARGET_RPC_LATENCY¶

This is the maximum amount of time the client will wait for a response from the server.

LLVM/OpenMP support for C library routines¶

Support for calling standard C library routines on GPU targets is provided by the LLVM C Library. This project provides two static libraries, libcgpu.a and libllvmlibc_rpc_server.a, which are used by the OpenMP runtime to provide libc support. The libcgpu.a library contains the GPU device code, while libllvmlibc_rpc_server.a provides the interface to the RPC interface. More information on the RPC construction can be found in the associated documentation.

To provide host services, we run an RPC server inside of the runtime. This allows the host to respond to requests made from the GPU asynchronously. For libc calls that require an RPC server, such as printing, an external handle to the RPC client running on the GPU will be present in the GPU executable. If we find this symbol, we will initialize a client and server and run it in the background while the kernel is executing.

For example, consider the following simple OpenMP offloading code. Here we will simply print a string to the user from the GPU.

#include <stdio.h>

int main() {
 #pragma omp target
   { fputs("Hello World!\n", stderr); }
}

We can compile this using the libcgpu.a library to resolve the symbols. Because this function requires RPC support, this will also pull in an externally visible symbol called __llvm_libc_rpc_client into the device image. When loading the device image, the runtime will check for this symbol and initialize an RPC interface if it is found. The following example shows the RPC server being used.

$ clang++ hello.c -fopenmp --offload-arch=gfx90a -lcgpu
$ env LIBOMPTARGET_DEBUG=1 ./a.out
PluginInterface --> Running an RPC server on device 0
...
Hello World!

LLVM/OpenMP Target Device Runtime (`libomptarget-ARCH-SUBARCH.bc`)¶

The target device runtime is an LLVM bitcode library that implements OpenMP runtime functions on the target device. It is linked with the device code’s LLVM IR during compilation.

Dynamic Shared Memory¶

The target device runtime contains a pointer to the dynamic shared memory buffer. This pointer can be obtained using the llvm_omp_target_dynamic_shared_alloc extension. If this function is called from the host it will simply return a null pointer. In order to use this buffer the kernel must be launched with an adequate amount of dynamic shared memory allocated. This can be done using the LIBOMPTARGET_SHARED_MEMORY_SIZE environment variable or the ompx_dyn_cgroup_mem(<N>) target directive clause. Examples for both are given below.

void foo() {
  int x;
#pragma omp target parallel map(from : x)
  {
    int *buf = llvm_omp_target_dynamic_shared_alloc();
    if (omp_get_thread_num() == 0)
      *buf = 1;
#pragma omp barrier
    if (omp_get_thread_num() == 1)
      x = *buf;
  }
  assert(x == 1);
}

$ clang++ -fopenmp --offload-arch=sm_80 -O3 shared.c
$ env LIBOMPTARGET_SHARED_MEMORY_SIZE=256 ./shared

void foo(int N) {
  int x;
#pragma omp target parallel map(from : x) ompx_dyn_cgroup_mem(N * sizeof(int))
  {
    int *buf = llvm_omp_target_dynamic_shared_alloc();
    if (omp_get_thread_num() == 0)
      buf[N - 1] = 1;
#pragma omp barrier
    if (omp_get_thread_num() == 1)
      x = buf[N - 1];
  }
  assert(x == 1);
}

$ clang++ -fopenmp --offload-arch=gfx90a -O3 shared.c
$ env ./shared

Device Allocation¶

The device runtime supports basic runtime allocation via the omp_alloc function. Currently, this allocates global memory for all default traits. Access modifiers are currently not supported and return a null pointer.

Debugging¶

The device runtime supports debugging in the runtime itself. This is configured at compile-time using the flag -fopenmp-target-debug=<N> rather than using a separate debugging build. If debugging is not enabled, the debugging paths will be considered trivially dead and removed by the compiler with zero overhead. Debugging is enabled at runtime by running with the environment variable LIBOMPTARGET_DEVICE_RTL_DEBUG=<N> set. The number set is a 32-bit field used to selectively enable and disable different features. Currently, the following debugging features are supported.

Enable debugging assertions in the device. 0x01

Enable diagnosing common problems during offloading . 0x4

Enable device malloc statistics (amdgpu only). 0x8

LLVM/OpenMP Runtimes¶

LLVM/OpenMP Host Runtime (libomp)¶

Environment Variables¶

OMP_CANCELLATION¶

OMP_DISPLAY_ENV¶

OMP_DEFAULT_DEVICE¶

OMP_DYNAMIC¶

OMP_MAX_ACTIVE_LEVELS¶

OMP_NESTED¶

OMP_NUM_THREADS¶

OMP_PLACES¶

OMP_PROC_BIND (Windows, Linux)¶

OMP_SCHEDULE¶

OMP_STACKSIZE¶

OMP_THREAD_LIMIT¶

OMP_WAIT_POLICY¶

KMP_AFFINITY (Windows, Linux)¶

KMP_HIDDEN_HELPER_AFFINITY (Windows, Linux)¶

KMP_ALL_THREADS¶

KMP_BLOCKTIME¶

KMP_CPUINFO_FILE¶

KMP_DETERMINISTIC_REDUCTION¶

KMP_DYNAMIC_MODE¶

KMP_HOT_TEAMS_MAX_LEVEL¶

KMP_HOT_TEAMS_MODE¶

KMP_HW_SUBSET¶

KMP_INHERIT_FP_CONTROL¶

KMP_LIBRARY¶

KMP_SETTINGS¶

KMP_STACKSIZE¶

KMP_TOPOLOGY_METHOD¶

KMP_VERSION¶

KMP_WARNINGS¶

LLVM/OpenMP Target Host Runtime (libomptarget)¶

Environment Variables¶

LIBOMPTARGET_DEBUG¶

LIBOMPTARGET_PROFILE¶

LIBOMPTARGET_PROFILE_GRANULARITY¶

LIBOMPTARGET_MEMORY_MANAGER_THRESHOLD¶

LIBOMPTARGET_INFO¶

Errors:¶

LIBOMPTARGET_STACK_SIZE¶

LIBOMPTARGET_HEAP_SIZE¶

LIBOMPTARGET_SHARED_MEMORY_SIZE¶

LIBOMPTARGET_MAP_FORCE_ATOMIC¶

LIBOMPTARGET_JIT_OPT_LEVEL¶

LIBOMPTARGET_JIT_SKIP_OPT¶

LIBOMPTARGET_JIT_REPLACEMENT_OBJECT¶

LIBOMPTARGET_JIT_REPLACEMENT_MODULE¶

LIBOMPTARGET_JIT_PRE_OPT_IR_MODULE¶

LIBOMPTARGET_JIT_POST_OPT_IR_MODULE¶

LIBOMPTARGET_MIN_THREADS_FOR_LOW_TRIP_COUNT¶

LIBOMPTARGET_REUSE_BLOCKS_FOR_HIGH_TRIP_COUNT¶

OFFLOAD_TRACK_ALLOCATION_TRACES¶

OFFLOAD_TRACK_KERNEL_LAUNCH_TRACES¶

LLVM/OpenMP Target Host Runtime Plugins (libomptarget.rtl.XXXX)¶

Environment Variables¶

LIBOMPTARGET_NUM_INITIAL_STREAMS¶

LIBOMPTARGET_NUM_INITIAL_EVENTS¶

LIBOMPTARGET_LOCK_MAPPED_HOST_BUFFERS¶

LIBOMPTARGET_AMDGPU_NUM_HSA_QUEUES¶

LIBOMPTARGET_AMDGPU_HSA_QUEUE_SIZE¶

LIBOMPTARGET_AMDGPU_HSA_QUEUE_BUSY_TRACKING¶

LIBOMPTARGET_AMDGPU_TEAMS_PER_CU¶

LIBOMPTARGET_AMDGPU_MAX_ASYNC_COPY_BYTES¶

LIBOMPTARGET_AMDGPU_NUM_INITIAL_HSA_SIGNALS¶

LIBOMPTARGET_AMDGPU_STREAM_BUSYWAIT¶

Remote Offloading Plugin:¶

LIBOMPTARGET_RPC_ADDRESS¶

LIBOMPTARGET_RPC_ALLOCATOR_MAX¶

LIBOMPTARGET_BLOCK_SIZE¶

LIBOMPTARGET_RPC_LATENCY¶

LLVM/OpenMP support for C library routines¶

LLVM/OpenMP Target Device Runtime (libomptarget-ARCH-SUBARCH.bc)¶

Dynamic Shared Memory¶

Device Allocation¶

Debugging¶

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LLVM/OpenMP Host Runtime (`libomp`)¶

LLVM/OpenMP Target Host Runtime (`libomptarget`)¶

LLVM/OpenMP Target Host Runtime Plugins (`libomptarget.rtl.XXXX`)¶

LLVM/OpenMP Target Device Runtime (`libomptarget-ARCH-SUBARCH.bc`)¶