Intel® FPGA SDK for OpenCL™ Pro Edition: Programming Guide

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ID 683846
Date 12/19/2022
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Document Table of Contents
Document Table of Contents x
Product Discontinuance Notification 1. Intel® FPGA SDK for OpenCL™ Overview 2. Intel® FPGA SDK for OpenCL™ Offline Compiler Kernel Compilation Flows 3. Obtaining General Information on Software, Compiler, and Custom Platform 4. Managing an FPGA Board 5. Structuring Your OpenCL Kernel 6. Designing Your Host Application 7. Compiling Your OpenCL Kernel 8. Emulating and Debugging Your OpenCL Kernel 9. Developing OpenCL Applications Using Third-party IDEs 10. Developing OpenCL™ Applications Using Intel® Code Builder for OpenCL™ 11. Intel® FPGA SDK for OpenCL™ Advanced Features A. Support Statuses of OpenCL Features B. Intel FPGA SDK for OpenCL Pro Edition Programming Guide Archives C. Document Revision History of the Intel® FPGA SDK for OpenCL™ Pro Edition Programming Guide
1. Intel® FPGA SDK for OpenCL™ Overview x
1.1. Intel® FPGA SDK for OpenCL™ Pro Edition Programming Guide Prerequisites 1.2. Intel® FPGA SDK for OpenCL™ FPGA Programming Flow
2. Intel® FPGA SDK for OpenCL™ Offline Compiler Kernel Compilation Flows x
2.1. One-Step Compilation for Simple Kernels 2.2. Multistep Intel® FPGA SDK for OpenCL™ Pro Edition Design Flow
3. Obtaining General Information on Software, Compiler, and Custom Platform x
3.1. Displaying the Software Version (version) 3.2. Displaying the Compiler Version (-version) 3.3. Listing the Intel® FPGA SDK for OpenCL™ Utility Command Options (help) 3.4. Listing the Intel® FPGA SDK for OpenCL™ Offline Compiler Command Options (no argument, -help, or -h) 3.5. Listing the Available FPGA Boards and Custom Platforms (-list-boards and -list-board-packages) 3.6. Displaying the Compilation Environment of an OpenCL Binary (env)
3.3. Listing the Intel® FPGA SDK for OpenCL™ Utility Command Options (help) x
3.3.1. Displaying Information on an Intel® FPGA SDK for OpenCL™ Utility Command Option (help <command_option>)
4. Managing an FPGA Board x
4.1. Installing an FPGA Board (install) 4.2. Uninstalling an FPGA Board (uninstall) 4.3. Querying the Device Name of Your FPGA Board (diagnose) 4.4. Running a Board Diagnostic Test (diagnose <device_name>) 4.5. Programming the FPGA Offline or without a Host (program <device_name>) 4.6. Programming the Flash Memory (flash <device_name>)
5. Structuring Your OpenCL Kernel x
5.1. Guidelines for Naming the Kernel 5.2. Programming Strategies for Optimizing Data Processing Efficiency 5.3. Programming Strategies for Optimizing Pointer-to-Local Memory Size 5.4. Implementing the Intel® FPGA SDK for OpenCL™ Channels Extension 5.5. Implementing OpenCL Pipes 5.6. Implementing Arbitrary Precision Integers 5.7. Using Predefined Preprocessor Macros in Conditional Compilation 5.8. Declaring __constant Address Space Qualifiers 5.9. Including Structure Data Types as Arguments in OpenCL Kernels 5.10. Inferring a Register 5.11. Enabling Double Precision Floating-Point Operations 5.12. Single-Cycle Floating-Point Accumulator for Single Work-Item Kernels 5.13. Integer Promotion Rules
5.2. Programming Strategies for Optimizing Data Processing Efficiency x
5.2.1. Unrolling a Loop (unroll Pragma) 5.2.2. Disabling Pipelining of a Loop (disable_loop_pipelining Pragma) 5.2.3. Coalescing Nested Loops 5.2.4. Fusing Adjacent Loops (loop_fuse Pragma) 5.2.5. Marking Loops to Prevent Automatic Fusion (nofusion Pragma) 5.2.6. Specifying a Loop Initiation interval (II) 5.2.7. Loop Concurrency (max_concurrency Pragma) 5.2.8. Loop Speculation (speculated_iterations Pragma) 5.2.9. Loop Interleaving Control (max_interleaving Pragma) 5.2.10. Floating Point Optimizations (fp contract and fp reassociate Pragma) 5.2.11. Specifying Work-Group Sizes 5.2.12. Specifying Number of Compute Units 5.2.13. Specifying Number of SIMD Work-Items 5.2.14. Specifying the private_copies Memory Attribute 5.2.15. Specifying the use_stall_enable_clusters Cluster-control Attribute
5.4. Implementing the Intel® FPGA SDK for OpenCL™ Channels Extension x
5.4.1. Overview of the Intel® FPGA SDK for OpenCL™ Channels Extension 5.4.2. Channel Data Behavior 5.4.3. Multiple Work-Item Ordering for Channels 5.4.4. Restrictions in the Implementation of Intel® FPGA SDK for OpenCL™ Channels Extension 5.4.5. Enabling the Intel® FPGA SDK for OpenCL™ Channels for OpenCL Kernel
5.4.3. Multiple Work-Item Ordering for Channels x
5.4.3.1. Work-Item Serial Execution of Channels
5.4.5. Enabling the Intel® FPGA SDK for OpenCL™ Channels for OpenCL Kernel x
5.4.5.1. Declaring the Channel Handle 5.4.5.2. Implementing Blocking Channel Writes 5.4.5.3. Implementing Blocking Channel Reads 5.4.5.4. Implementing I/O Channels Using the io Channels Attribute 5.4.5.5. Emulating I/O Channels 5.4.5.6. Use Models of Intel® FPGA SDK for OpenCL™ Channels Implementation 5.4.5.7. Implementing Buffered Channels Using the depth Channels Attribute 5.4.5.8. Enforcing the Order of Channel Calls
5.5. Implementing OpenCL Pipes x
5.5.1. Overview of the OpenCL Pipe Functions 5.5.2. Pipe Data Behavior 5.5.3. Multiple Work-Item Ordering for Pipes 5.5.4. Restrictions in OpenCL Pipes Implementation 5.5.5. Enabling OpenCL Pipes for Kernels 5.5.6. Direct Communication with Kernels via Host Pipes
5.5.3. Multiple Work-Item Ordering for Pipes x
5.5.3.1. Work-item Serial Execution of Pipes
5.5.5. Enabling OpenCL Pipes for Kernels x
5.5.5.1. Ensuring Compatibility with Other OpenCL SDKs 5.5.5.2. Declaring the Pipe Handle 5.5.5.3. Implementing Pipe Writes 5.5.5.4. Implementing Pipe Reads 5.5.5.5. Implementing Buffered Pipes Using the depth Attribute 5.5.5.6. Implementing I/O Pipes Using the io Attribute 5.5.5.7. Enforcing the Order of Pipe Calls
5.5.6. Direct Communication with Kernels via Host Pipes x
5.5.6.1. Optional intel_host_accessible Kernel Argument Attribute 5.5.6.2. API Functions for Interacting with cl_mem Pipe Objects Bound to Host-Accessible Pipe Kernel Arguments clReadPipeIntelFPGA Function clWritePipeIntelFPGA Function clMapHostPipeIntelFPGA Function clUnmapHostPipeIntelFPGA Function Recommendations for Using Host Pipes Efficiently Recommendations for Avoiding Hangs, Stalls or Deadlocks 5.5.6.3. Creating a Host Accessible Pipe 5.5.6.4. Example Use of the cl_intel_fpga_host_pipe Extension
5.9. Including Structure Data Types as Arguments in OpenCL Kernels x
5.9.1. Matching Data Layouts of Host and Kernel Structure Data Types 5.9.2. Disabling Insertion of Data Structure Padding 5.9.3. Specifying the Alignment of a Struct
5.10. Inferring a Register x
5.10.1. Inferring a Shift Register
5.12. Single-Cycle Floating-Point Accumulator for Single Work-Item Kernels x
5.12.1. Programming Strategies for Inferring the Accumulator
6. Designing Your Host Application x
6.1. Host Programming Requirements 6.2. Allocating OpenCL Buffers for Manual Partitioning of Global Memory 6.3. Triggering Collection Profiling Data During Kernel Execution 6.4. Accessing Custom Platform-Specific Functions 6.5. Modifying Host Program for Structure Parameter Conversion 6.6. Managing Host Application 6.7. Allocating Shared Memory for OpenCL Kernels Targeting SoCs 6.8. Sharing Multiple Devices Across Multiple Host Programs
6.1. Host Programming Requirements x
6.1.1. Host Machine Memory Requirements 6.1.2. Host Binary Requirement 6.1.3. Multiple Host Threads 6.1.4. Out-of-order Command Queues 6.1.5. Requirement for Multiple Command Queues to Execute Kernels Concurrently
6.2. Allocating OpenCL Buffers for Manual Partitioning of Global Memory x
6.2.1. Partitioning Buffers Across Multiple Interfaces of the Same Memory Type 6.2.2. Partitioning Buffers Across Different Memory Types (Heterogeneous Memory) 6.2.3. Creating a Pipe Object in Your Host Application 6.2.4. Enabling All Global Memory
6.3. Triggering Collection Profiling Data During Kernel Execution x
6.3.1. Profiling Autorun Kernels 6.3.2. Profile Data Acquisition
6.3.1. Profiling Autorun Kernels x
6.3.1.1. Multiple Autorun Profiling Calls
6.6. Managing Host Application x
6.6.1. Displaying Example Makefile Fragments (example-makefile or makefile) 6.6.2. Compiling and Linking Your Host Application 6.6.3. Using OpenCL ICD Extension APIs 6.6.4. Programming an FPGA via the Host 6.6.5. Termination of the Runtime Environment and Error Recovery
6.6.2. Compiling and Linking Your Host Application x
6.6.2.1. Linking Your Host Application to the Khronos ICD Loader Library 6.6.2.2. Displaying Flags for Compiling Host Application (compile-config) 6.6.2.3. Displaying Paths to OpenCL Host Runtime and MMD Libraries (ldflags) 6.6.2.4. Listing OpenCL Host Runtime and MMD Libraries (ldlibs) 6.6.2.5. Displaying Information on OpenCL Host Runtime and MMD Libraries (link-config or linkflags)
6.6.4. Programming an FPGA via the Host x
6.6.4.1. Programming Multiple FPGA Devices
7. Compiling Your OpenCL Kernel x
7.1. Compiling Your Kernel to Create Hardware Configuration File 7.2. Compiling Your Kernel without Building Hardware (-c) 7.3. Compiling and Linking Your Kernels or Object Files without Building Hardware (-rtl) 7.4. Specifying the Location of Header Files (-I=<directory>) 7.5. Specifying the Name of an Intel® FPGA SDK for OpenCL™ Offline Compiler Output File (-o <filename>) 7.6. Compiling a Kernel for a Specific FPGA Board and Custom Platform (-board=<board_name>) and (-board-package=<board_package_path>) 7.7. Resolving Hardware Generation Fitting Errors during Kernel Compilation (-high-effort) 7.8. Specifying Schedule Fmax Target for Kernels (-clock=<clock_target>) 7.9. Defining Preprocessor Macros to Specify Kernel Parameters (-D<macro_name>) 7.10. Generating Compilation Progress Report (-v) 7.11. Displaying the Estimated Resource Usage Summary On-Screen (-report) 7.12. Suppressing Warning Messages from the Intel® FPGA SDK for OpenCL™ Offline Compiler (-W) 7.13. Converting Warning Messages from the Intel® FPGA SDK for OpenCL™ Offline Compiler into Error Messages (-Werror) 7.14. Removing Debug Data from Compiler Reports and Source Code from the .aocx File (-g0) 7.15. Disabling Burst-Interleaving of Global Memory (-no-interleaving=<global_memory_type>) 7.16. Forcing Ring Interconnect for Global Memory (-global-ring) 7.17. Forcing a Single Store Ring to Reduce Area at the Expense of Write Throughput to Global Memory (-force-single-store-ring) 7.18. Forcing Fewer Read Data Reorder Units to Reduce Area at the Expense of Read Throughput to Global Memory (-num-reorder) 7.19. Configuring Constant Memory Cache Size (-const-cache-bytes=<N>) 7.20. Relaxing the Order of Floating-Point Operations (-ffp-reassociate) 7.21. Reducing Floating-Point Rounding Operations (-ffp-contract=fast) 7.22. Speeding Up Your OpenCL Compilation (-fast-compile) 7.23. Compiling Your Kernel Incrementally (-incremental) 7.24. Compiling Your Kernel with Memory Error Correction Coding (-ecc) 7.25. Disabling Hardware Kernel Invocation Queue (-no-hardware-kernel-invocation-queue) 7.26. Modifying the Handshaking Protocol (-hyper-optimized-handshaking) 7.27. Pipelining Loops in Non-task Kernels (-auto-pipeline)
7.23. Compiling Your Kernel Incrementally (-incremental) x
7.23.1. The Incremental Compile Report 7.23.2. Additional Command Options for Incremental Compilation 7.23.3. Limitations of the Incremental Compilation Feature
8. Emulating and Debugging Your OpenCL Kernel x
8.1. Setting up the Emulator 8.2. Modifying Channels Kernel Code for Emulation 8.3. Compiling a Kernel for Emulation (-march=emulator) 8.4. Emulating Your OpenCL Kernel 8.5. Debugging Your OpenCL Kernel on Linux 8.6. Limitations of the Intel® FPGA SDK for OpenCL™ Emulator 8.7. Discrepancies in Hardware and Emulator Results 8.8. Emulator Environment Variables 8.9. Extensions Supported by the Emulator 8.10. Emulator Known Issues
8.2. Modifying Channels Kernel Code for Emulation x
8.2.1. Emulating a Kernel that Passes Pipes or Channels by Value 8.2.2. Emulating Channel Depth 8.2.3. Emulating Applications with a Channel That Reads or Writes to an I/O Channel
9. Developing OpenCL Applications Using Third-party IDEs x
9.1. FPGA Workflows in Microsoft Visual Studio 9.2. FPGA Workflows in Eclipse 9.3. Limitations
9.1. FPGA Workflows in Microsoft Visual Studio x
9.1.1. Preparing the Visual Studio Environment 9.1.2. Creating an FPGA OpenCL Template 9.1.3. Configuring the Build Targets 9.1.4. Configuring Build Options for a Project 9.1.5. Generating the High-level Design Report 9.1.6. Building and Running the FPGA Template
9.2. FPGA Workflows in Eclipse x
9.2.1. Preparing the Eclipse Environment 9.2.2. Creating a Simple FPGA application 9.2.3. Creating a Makefile Project 9.2.4. Building a Project
9.2.2. Creating a Simple FPGA application x
9.2.2.1. Creating a Project 9.2.2.2. Reviewing the Code and Building the Project 9.2.2.3. Running the Application
10. Developing OpenCL™ Applications Using Intel® Code Builder for OpenCL™ x
10.1. Configuring the Intel® Code Builder for OpenCL™ Offline Compiler Plug-in for Microsoft Visual Studio 10.2. Configuring the Intel® Code Builder for OpenCL™ Offline Compiler Plug-in for Eclipse 10.3. Creating a Session in the Intel® Code Builder for OpenCL™ 10.4. Configuring a Session
11. Intel® FPGA SDK for OpenCL™ Advanced Features x
11.1. OpenCL Library 11.2. Memory Attributes for Configuring Kernel Memory Systems 11.3. Kernel Attributes for Reducing the Overhead on Hardware Usage 11.4. Kernel Replication Using the num_compute_units(X,Y,Z) Attribute 11.5. Intra-Kernel Registered Assignment Built-In Function
11.1. OpenCL Library x
11.1.1. Creating Library Objects From OpenCL Code 11.1.2. Understanding RTL Modules and the OpenCL Pipeline 11.1.3. Packaging an OpenCL Helper Function File for an OpenCL Library 11.1.4. Packaging an RTL Component for an OpenCL Library 11.1.5. Verifying the RTL Modules 11.1.6. Specifying an OpenCL Library when Compiling an OpenCL Kernel 11.1.7. Debugging Your OpenCL Library Through Simulation (Preview) 11.1.8. Using an OpenCL Library that Works with Simple Functions (Example 1) 11.1.9. Using an OpenCL Library that Works with External Memory (Example 2) 11.1.10. OpenCL Library Command-Line Options
11.1.1. Creating Library Objects From OpenCL Code x
11.1.1.1. Creating an Object File From OpenCL Code 11.1.1.2. Packaging Object Files into a Library File
11.1.2. Understanding RTL Modules and the OpenCL Pipeline x
11.1.2.1. Overview: Intel FPGA SDK for OpenCL Pipeline Approach 11.1.2.2. Integration of an RTL Module into the Intel FPGA SDK for OpenCL Pipeline 11.1.2.3. Stall-Free RTL 11.1.2.4. RTL Module Interfaces 11.1.2.5. Avalon Streaming Interface 11.1.2.6. RTL Reset and Clock Signals 11.1.2.7. Object Manifest File Syntax of an RTL Module 11.1.2.8. Interaction between RTL Module and External Memory 11.1.2.9. Order of Threads Entering an RTL Module 11.1.2.10. OpenCL C Model of an RTL Module 11.1.2.11. Potential Incompatibility between RTL Modules and Partial Reconfiguration
11.1.2.6. RTL Reset and Clock Signals x
11.1.2.6.1. Intel® Stratix® 10 Design-Specific Reset Requirements for Stall-Free and Stallable RTL Modules
11.1.2.7. Object Manifest File Syntax of an RTL Module x
11.1.2.7.1. XML Elements for ATTRIBUTES 11.1.2.7.2. XML Elements for INTERFACE 11.1.2.7.3. XML Elements for RESOURCES
11.1.4. Packaging an RTL Component for an OpenCL Library x
11.1.4.1. Restrictions and Limitations in RTL Support for the Intel® FPGA SDK for OpenCL™ Library Feature
11.1.7. Debugging Your OpenCL Library Through Simulation (Preview) x
11.1.7.1. Compiling a Library for Simulation (-march=simulator) 11.1.7.2. Simulating Your OpenCL* Library 11.1.7.3. Troubleshooting Simulator Issues
11.2. Memory Attributes for Configuring Kernel Memory Systems x
11.2.1. Restrictions on the Use of Variable-specific Attributes
11.3. Kernel Attributes for Reducing the Overhead on Hardware Usage x
11.3.1. Hardware for Kernel Interface
11.3.1. Hardware for Kernel Interface x
11.3.1.1. Omit Hardware that Generates and Dispatches Kernel IDs 11.3.1.2. Omit Communication Hardware between the Host and the Kernel 11.3.1.3. Omit Hardware to Support the global_work_offset Argument in the clEnqueueNDRangeKernel API
11.4. Kernel Replication Using the num_compute_units(X,Y,Z) Attribute x
11.4.1. Customization of Replicated Kernels Using the get_compute_id() Function 11.4.2. Using Channels with Kernel Copies
A. Support Statuses of OpenCL Features x
A.1. Support Statuses of OpenCL 1.0 Features A.2. Support Statuses of OpenCL 1.2 Features A.3. Support Statuses of OpenCL 2.0 Features A.4. Intel® FPGA SDK for OpenCL™ Allocation Limits
A.1. Support Statuses of OpenCL 1.0 Features x
A.1.1. OpenCL 1.0 C Programming Language Implementation A.1.2. OpenCL C Programming Language Restrictions A.1.3. Argument Types for Built-in Geometric Functions A.1.4. Numerical Compliance Implementation A.1.5. Image Addressing and Filtering Implementation A.1.6. Atomic Functions A.1.7. Embedded Profile Implementation
A.2. Support Statuses of OpenCL 1.2 Features x
A.2.1. OpenCL 1.2 Runtime Implementation A.2.2. OpenCL 1.2 C Programming Language Implementation
A.3. Support Statuses of OpenCL 2.0 Features x
A.3.1. OpenCL 2.0 Headers A.3.2. OpenCL 2.0 Runtime Implementation A.3.3. OpenCL 2.0 C Programming Language Restrictions for Pipes
Product Discontinuance Notification
1. Intel® FPGA SDK for OpenCL™ Overview
2. Intel® FPGA SDK for OpenCL™ Offline Compiler Kernel Compilation Flows
3. Obtaining General Information on Software, Compiler, and Custom Platform
4. Managing an FPGA Board
5. Structuring Your OpenCL Kernel
6. Designing Your Host Application
7. Compiling Your OpenCL Kernel
8. Emulating and Debugging Your OpenCL Kernel
9. Developing OpenCL Applications Using Third-party IDEs
10. Developing OpenCL™ Applications Using Intel® Code Builder for OpenCL™
11. Intel® FPGA SDK for OpenCL™ Advanced Features
A. Support Statuses of OpenCL Features
B. Intel FPGA SDK for OpenCL Pro Edition Programming Guide Archives
C. Document Revision History of the Intel® FPGA SDK for OpenCL™ Pro Edition Programming Guide

5.5.6.2. API Functions for Interacting with cl_mem Pipe Objects Bound to Host-Accessible Pipe Kernel Arguments

Including the clReadPipeIntelFPGA, clWritePipeIntelFPGA, clMapHostPipeIntelFPGA, and clUnmapHostPipeIntelFPGA host API functions allows the host program to read from and write to the cl_mem pipe objects that have been bound (using clSetKernelArg argument) to host-accessible pipe kernel arguments.
  • clReadPipeIntelFPGA and clWritePipeIntelFPGA functions operate on single words of the pipe’s width.
  • clMapHostPipeIntelFPGA function is an advanced mechanism to reduce latency and overhead when performing many word reads or writes on a host pipe.
  • clUnmapHostPipeIntelFPGA function allows the host program to signal to the OpenCL runtime that it has written to or read from either a portion of or the entire mapped region that was created through a previous clMapHostPipeIntelFPGA function call.

The following sections describe the API functions for bound cl_mem objects:

clReadPipeIntelFPGA Function

This function reads a data packet from a pipe with the following characteristics:

  • Created with the CL_MEM_HOST_READ_ONLY flag.
  • Bound to a kernel argument that has the write_only definition and the intel_host_accessible kernel argument attribute.

Each clReadPipeIntelFPGA function call reads one packet from the pipe. The operation is non-blocking. It does not wait until data is available in the pipe to successfully read before returning.

Syntax 
cl_int clReadPipeIntelFPGA (cl_mem pipe, 
                            gentype *ptr);

Return Values

The clReadPipeIntelFPGA function returns CL_SUCCESS if the read is successful. Otherwise, it returns one of the following errors:

Table 4.  Return Values for clReadPipeIntelFPGA Function
Return Value Description
CL_INVALID_MEM_OBJECT Pipe was not created with the clCreatePipe function or if the CL_MEM_HOST_READ_ONLY flag is not used when creating the pipe.
CL_INVALID_KERNEL Pipe is not bound to a kernel argument using the clSetKernelArg function.
CL_INVALID_VALUE The ptr attribute is NULL.
CL_PIPE_EMPTY Pipe is empty with no data, and therefore there were no valid packets to read.

clWritePipeIntelFPGA Function

This function writes a data packet to a pipe with the following characteristics:

  • Created with the CL_MEM_HOST_WRITE_ONLY flag.
  • Bound to a kernel argument that has the read_only definition and the intel_host_accessible kernel argument attribute.

Each clWritePipeIntelFPGA function call writes one packet to the pipe. The operation is non-blocking. It does not wait until there is a capacity in the pipe to successfully write before returning. A return status of CL_SUCCESS does not imply that data is available to the kernel for reading. Data eventually is available for reading by the kernel, assuming that any previously mapped buffers on the host pipe are unmapped.

Syntax 
cl_int clWritePipeIntelFPGA (cl_mem pipe, 
                             gentype *ptr);

Return Values

The clWritePipeIntelFPGA function returns CL_SUCCESS if the write is successful. Otherwise, it returns one of the following errors:

Table 5.  Return Values for clWritePipeIntelFPGA Function
Return Value Description
CL_INVALID_MEM_OBJECT Pipe is not created with clCreatePipe function or if the CL_MEM_HOST_WRITE_ONLY flag is not used when creating the pipe.
CL_INVALID_KERNEL Pipe is not bound to a kernel argument using the clSetKernelArg function.
CL_INVALID_VALUE The ptr attribute is NULL.
CL_PIPE_FULL Pipe is already full of data and cannot accept further packets without one being read by a kernel. The packet capacity of the pipe is specified as an argument to the clCreatePipe function.

clMapHostPipeIntelFPGA Function

This function returns a void * in the host address space. The pipe can write data to this address space if it was created with the CL_MEM_HOST_WRITE_ONLY flag. The pipe can read data from this address space if it was created with the CL_MEM_HOST_READ_ONLY flag.

The mapped_size argument specifies the maximum number of bytes that the host can access, as determined by the runtime in the memory. The value specified by mapped_size argument is less than or equal to the value of the requested_size argument that the caller specifies.

After writing to or reading from the returned void *, the host must execute one or more clUnmapHostPipeIntelFPGA function calls to signal to the runtime that data is ready for transfer to the device (on a write) and that the runtime can reclaim the memory for reuse (on a read or write). If the clMapHostPipeIntelFPGA function is called before the clUnmapHostPipeIntelFPGA function unmaps all memory mapped by a previous clMapHostPipeIntelFPGA function call, the buffer returned by the second clMapHostPipeIntelFPGA call does not overlap with that returned by the first call.

Syntax 
void * clMapHostPipeIntelFPGA (cl_mem pipe,
                               cl_map_flags map_flags,
                               size_t requested_size,
                               size_t * mapped_size,
                               cl_int * errcode_ret);

Return Values

The clMapHostPipeIntelFPGA function returns a valid non-NULL address and CL_SUCCESS is returned in errcode_ref if the host pipe is mapped successfully. Otherwise, it returns NULL and errcode_ret is set with one of the following values:

Table 6.  Error Values Set in errcode_ret
Description Error Values
This error is returned when the:
  • Pipe is not created with the clCreatePipe function.
  • CL_MEM_HOST_WRITE_ONLY or CL_MEM_HOST_READ_ONLY flag is not used when creating a pipe.
  • Pipe has been released.
 CL_INVALID_MEM_OBJECT
Pipe is not bound to a kernel argument using the clSetKernelArg function. CL_INVALID_KERNEL
The requested_size attribute is not a multiple of the packet size that is specified to the clCreatePipe function. CL_INVALID_VALUE
The mapped_size attribute is NULL.
Runtime cannot provide buffer space for the host to read or write. This may occur when a new mapping is requested before data is transferred to or from the device from a previous clUnmapHostPipeIntelFPGA function call, so attempting to map again may succeed. CL_OUT_OF_RESOURCES
Runtime is unable to allocate the host addressable memory. CL_OUT_OF_HOST_MEMORY

clUnmapHostPipeIntelFPGA Function

This function signals to the runtime that the host no longer uses size_to_unmap bytes of a host-addressable buffer that the clMapHostPipeIntelFPGA function has returned previously. In the case of a writeable host pipe, calling the clUnmapHostPipeIntelFPGA function allows the unmapped data to become available to the kernel. If the size_to_unmap value is smaller than the mapped_size value specified by the clMapHostPipeIntelFPGA function, then multiple clUnmapHostPipeIntelFPGA function calls are necessary to unmap full capacity of the buffer. You may include multiple clUnmapHostPipeIntelFPGA function calls to unmap successive bytes in the buffer returned by a clMapHostPipeIntelFPGA function call, up to the mapped_size value defined by the clMapHostPipeIntelFPGA call.

Syntax 
cl_int clUnmapHostPipeIntelFPGA (cl_mem pipe, 
                                 void * mapped_ptr,
                                 size_t size_to_unmap,
                                 size_t * unmapped_size);

Return Values

The clUnmapHostPipeIntelFPGA function returns CL_SUCCESS on successful unmapping. Otherwise, it returns the following error:

Table 7.  Return Values for clUnmapHostPipeIntelFPGA Function
Return Value Description
CL_INVALID_VALUE The mapped_ptr attribute is not a valid pointer returned by a clMapHostPipeIntelFPGA function call associated with the pipe, or if the mapped_ptr has already been fully unmapped.
The requested_size attribute is not a multiple of the packet size that was specified to the clCreatePipe function.
The requested_size attribute is larger than the remaining unmapped bytes in the mapped_ptr buffer.
The unmapped_size attribute is NULL.

Recommendations for Using Host Pipes Efficiently

To use host pipes efficiently, Intel® recommends the following:

  • Use map or unmap with multiple packets rather than single packet with read or write.
  • Use two threads to simultaneously map and unmap.
  • Ensure kernel can read or write data to host pipe in every clock cycle.

Recommendations for Avoiding Hangs, Stalls or Deadlocks

To avoid hangs, stalls, or deadlocks situation, Intel® recommends the following:

  • Packets may get lost when enqueuing kernels from different cl_programs. Use a single cl_program object in the host application.
  • Ensure that the same amount of data is written and read on kernel and host.
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