Intel® High Level Synthesis Compiler Pro Edition: Reference Manual

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Date 10/04/2021
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Document Table of Contents
Document Table of Contents x
1. Intel® HLS Compiler Pro Edition Reference Manual 2. Compiler 3. C Language and Library Support 4. Component Interfaces 5. Component Memories (Memory Attributes) 6. Loops in Components 7. Component Concurrency 8. Arbitrary Precision Math Support 9. Component Target Frequency 10. Systems of Tasks 11. Libraries 12. Advanced Hardware Synthesis Controls 13. Intel® High Level Synthesis Compiler Pro Edition Reference Summary A. Advanced Math Source Code Libraries B. Supported Math Functions C. Cyclone® V Restrictions D. Intel® HLS Compiler Pro Edition Reference Manual Archives E. Document Revision History of the Intel® HLS Compiler Pro Edition Reference Manual
2. Compiler x
2.1. Intel® HLS Compiler Pro Edition Command Options 2.2. Using Libraries in Your Component 2.3. Compiler Interoperability 2.4. Intel® HLS Compiler Hardware Model
2.3. Compiler Interoperability x
2.3.1. Compiling Your Testbench and Component Separately
3. C Language and Library Support x
3.1. Supported C and C++ Subset for Component Synthesis 3.2. C and C++ Libraries 3.3. Templated and Overloaded Functions 3.4. Intel® HLS Compiler Pro Edition Compiler-Defined Preprocessor Macros
3.3. Templated and Overloaded Functions x
3.3.1. Templated Functions 3.3.2. Overloaded Functions 3.3.3. Function Name Mapping
4. Component Interfaces x
4.1. Component Invocation Interface 4.2. Avalon® Streaming Interfaces 4.3. Pipes 4.4. Avalon® Memory-Mapped Host Interfaces 4.5. Agent Interfaces 4.6. Stable Component Parameters 4.7. Global Variables 4.8. Structs in Component Interfaces 4.9. Reset Behavior
4.1. Component Invocation Interface x
4.1.1. Scalar Parameters 4.1.2. Pointer and Reference Parameters 4.1.3. Interface Definition Example: Component Invocation Interface Control Attributes 4.1.4. Interface Definition Example: Component with Both Scalar and Pointer Arguments
4.3. Pipes x
Pipe Properties Pipe Accessors Data Persistence in Pipes Restrictions on using Pipes 4.3.1. The pipe Class and Its Use
4.4. Avalon® Memory-Mapped Host Interfaces x
4.4.1. Memory-Mapped Host Testbench Constructor 4.4.2. Implicit and Explicit Examples of Describing a Memory Interface 4.4.3. Avalon® Memory-Mapped Host Interfaces and Load-Store Units
4.4.3. Avalon® Memory-Mapped Host Interfaces and Load-Store Units x
4.4.3.1. Load-Store Unit Types 4.4.3.2. Memory-Access Coalescing and Load-Store Units
4.5. Agent Interfaces x
4.5.1. Control and Status Register (CSR) Agent 4.5.2. Agent Memories
5. Component Memories (Memory Attributes) x
5.1. Static Variables
6. Loops in Components x
6.1. Loop Initiation Interval (ii Pragma) 6.2. Loop-Carried Dependencies (ivdep Pragma) 6.3. Loop Coalescing (loop_coalesce Pragma) 6.4. Loop Unrolling (unroll Pragma) 6.5. Loop Concurrency (max_concurrency Pragma) 6.6. Loop Iteration Speculation (speculated_iterations Pragma) 6.7. Loop Pipelining Control (disable_loop_pipelining Pragma) 6.8. Loop Interleaving Control (max_interleaving Pragma) 6.9. Loop Fusion
6.9. Loop Fusion x
6.9.1. Loop Fusion Control (loop_fuse Pragma) 6.9.2. Loop Fusion Exemption (nofusion pragma)
7. Component Concurrency x
7.1. Serial Equivalence within a Memory Space or I/O 7.2. Concurrency Control (hls_max_concurrency Attribute) 7.3. Component Pipelining Control (hls_disable_component_pipelining Attribute)
8. Arbitrary Precision Math Support x
8.1. Declaring ac_int Data Types 8.2. Declaring ac_fixed Data Types 8.3. Declaring ac_complex Data Types 8.4. AC Data Types and Native Compilers 8.5. Declaring hls_float Data Types
8.1. Declaring ac_int Data Types x
8.1.1. Important Usage Information on the ac_int Data Type 8.1.2. Integer Promotion and ac_int Data Types 8.1.3. Debugging Your Use of the ac_int Data Type
8.2. Declaring ac_fixed Data Types x
8.2.1. Arbitrary Precision Fixed-Point Literals in Operations
8.5. Declaring hls_float Data Types x
8.5.1. Operators and Return Types Supported by the hls_float Data Type 8.5.2. Additional Data Types Provided By hls_float.h
9. Component Target Frequency x
9.1. Effects of Specifying Target II and Target fMAX
10. Systems of Tasks x
10.1. Task Functions 10.2. Internal Streams 10.3. System of Tasks Simulation
11. Libraries x
11.1. Static-Object Libraries 11.2. Creating a Static-Object Library 11.3. Creating Objects From HLS Code 11.4. Creating Objects From RTL Code 11.5. Packaging Object Files Into a Library
11.3. Creating Objects From HLS Code x
11.3.1. Creating an Object File From HLS Code 11.3.2. Supported OpenCL* Language Constructs
11.4. Creating Objects From RTL Code x
11.4.1. RTL Modules and the HLS Pipeline 11.4.2. Creating a Static-Object File from an RTL Module
11.4.1. RTL Modules and the HLS Pipeline x
11.4.1.1. Integration of an RTL Module into the HLS Pipeline 11.4.1.2. RTL Module Interfaces 11.4.1.3. RTL Reset and Clock Signals 11.4.1.4. Object Manifest File Syntax 11.4.1.5. Mapping HLS Data Types to RTL Signals 11.4.1.6. HLS Emulation Models for RTL-Based Functions 11.4.1.7. Potential Incompatibility between RTL Modules and Partial Reconfiguration 11.4.1.8. Stall-Free RTL 11.4.1.9. RTL Module Restrictions and Limitations for HLS Libraries
11.4.1.2. RTL Module Interfaces x
11.4.1.2.1. RTL Module Interface Signals
11.4.1.3. RTL Reset and Clock Signals x
11.4.1.3.1. Intel® Agilex™ and Intel® Stratix® 10 Design-Specific Reset Requirements for Stall-Free and Stallable RTL Modules
11.4.1.4. Object Manifest File Syntax x
11.4.1.4.1. XML Elements for ATTRIBUTES 11.4.1.4.2. XML Elements for INTERFACE 11.4.1.4.3. XML Elements for RESOURCES
11.4.1.4.1. XML Elements for ATTRIBUTES x
11.4.1.4.1.1. Interaction Between ALLOW_MERGINGand HAS_SIDE_EFFECTS Elements
12. Advanced Hardware Synthesis Controls x
12.1. Hardware Implementation Control for Math Functions 12.2. The hls_fpga_reg() Function
12.1. Hardware Implementation Control for Math Functions x
12.1.1. Math Function Hardware Implementation Summary 12.1.2. The --dsp-mode Command Option 12.1.3. The ihc::math_dsp_control Function
13. Intel® High Level Synthesis Compiler Pro Edition Reference Summary x
13.1. Intel® HLS Compiler Pro Edition i++ Command-Line Arguments 13.2. Intel® HLS Compiler Pro Edition Header Files 13.3. Intel® HLS Compiler Pro Edition Compiler-Defined Preprocessor Macros 13.4. Intel® HLS Compiler Pro Edition Keywords 13.5. Intel® HLS Compiler Pro Edition Simulation API (Testbench Only) 13.6. Intel® HLS Compiler Pro Edition Component Memory Attributes 13.7. Intel® HLS Compiler Pro Edition Loop Pragmas 13.8. Intel® HLS Compiler Pro Edition Scope Pragmas 13.9. Intel® HLS Compiler Pro Edition Component Attributes 13.10. Intel® HLS Compiler Pro Edition Component Default Interfaces 13.11. Intel® HLS Compiler Pro Edition Component Invocation Interface Control Attributes 13.12. Intel® HLS Compiler Pro Edition Component Macros 13.13. Intel® HLS Compiler Pro Edition Systems of Tasks API 13.14. Intel® HLS Compiler Pro Edition Pipes API 13.15. Intel® HLS Compiler Pro Edition Streaming Input Interfaces 13.16. Intel® HLS Compiler Pro Edition Streaming Output Interfaces 13.17. Intel® HLS Compiler Pro Edition Memory-Mapped Interfaces 13.18. Intel® HLS Compiler Pro Edition Load-Store Unit Control 13.19. Intel® HLS Compiler Pro Edition Arbitrary Precision Data Types
13.13. Intel® HLS Compiler Pro Edition Systems of Tasks API x
13.13.1. ihc::stream Class
A. Advanced Math Source Code Libraries x
A.1. Random Number Generator Library A.2. Matrix Multiplication Library A.3. Cholesky Decomposition Library
B. Supported Math Functions x
B.1. Math Functions Provided by the math.h Header File B.2. Math Functions Provided by the extendedmath.h Header File B.3. Math Functions Provided by the ac_fixed_math.h Header File B.4. Math Functions Provided by the hls_float.h Header File B.5. Math Functions Provided by the hls_float_math.h Header File B.6. Default Rounding Schemes and Subnormal Number Support
1. Intel® HLS Compiler Pro Edition Reference Manual
2. Compiler
3. C Language and Library Support
4. Component Interfaces
5. Component Memories (Memory Attributes)
6. Loops in Components
7. Component Concurrency
8. Arbitrary Precision Math Support
9. Component Target Frequency
10. Systems of Tasks
11. Libraries
12. Advanced Hardware Synthesis Controls
13. Intel® High Level Synthesis Compiler Pro Edition Reference Summary
A. Advanced Math Source Code Libraries
B. Supported Math Functions
C. Cyclone® V Restrictions
D. Intel® HLS Compiler Pro Edition Reference Manual Archives
E. Document Revision History of the Intel® HLS Compiler Pro Edition Reference Manual

4.3. Pipes

Using external memory to move data in and out of static-object libraries or task functions can constrain the performance of your design. Pipes provide a mechanism for passing data with high efficiency and low latency by using on-device FIFO buffers to communicate.

Pipes are similar to streams, but are simpler. You can use pipes in a component or to allow tasks to communicate with each other, but pipes support only ready/valid and data signals, while streams support additional sideband signals such as startofpacket and endofpacket.

Unlike streams, you can declare an array of pipes and you can iterate over the array to write or read many pipes in a design.

Data written to a pipe remains in the pipe until it is read or until the component is reset.

The memory model of pipes allows you to use them to send and receive data from task functions in running functions in a static-object library or a running task function.

Pipe Properties

Pipes have the following key properties:
FIFO ordering
Data is accessible (readable) only in FIFO order. There is no concept of a memory address or pointer in a pipe, which means random data access is not possible with pipes.
Capacity
Pipes have a capacity. That is, a fixed amount of data can be written to an initially empty pipe before needing to read anything from it to make room for more data.

A full pipe applies back pressure to the write site.

Pipe Accessors

Data is written to a pipe through an API that commits a single word of the pipe data type, and that word is later returned by an API that reads data from the pipe.

The API accessing the pipe can be a blocking or a nonblocking type:
Blocking API calls
Blocking write API calls wait until the pipe has enough capacity to commit data.

Blocking read API calls wait until the pipe contains data to be read.

Nonblocking API calls
Nonblocking API calls execute immediately and return a status that indicates whether the operation was successful.

You can mix blocking and nonblocking accesses to the same pipe. For example you can write data to a pipe with a blocking pipe write() call and read it from the other end using a non-blocking read() call, and vice versa.

Data Persistence in Pipes

Data written to a pipe by a component remains in the pipe until it is read or until the component is reset.

Data written to a pipe by a task remains in the pipe until another task reads from the pipe or the component containing the tasks is reset.

The sequence of data in a pipe always follows FIFO ordering.

Data in pipes does not persist across FPGA device resets or reprogramming.

Restrictions on using Pipes

Using pipes comes with the following restrictions:
Multiple pipe call sites
A component or task function can read from the same pipe multiple times, but multiple component or task functions cannot read from the same pipe. Similarly, a component or task function can write to the same pipe multiple times, but multiple component or task functions cannot write to the same pipe.
Feedback and feed-forward pipes
A component or task function should use separate pipes for pipe reads and pipe writes. Writing to and reading from the same pipe within the same function can lead to poor performance.
Pipe accesses in loops
Do not use nonblocking pipes if you use a loop structure that waits for data from the pipe. That is, avoid the following code pattern for nonblocking pipe accesses: 
bool success = false;
while (!success) {
  my_pipe::write(rd_src_buf[i], success); 
  // can also be a nonblocking read
}
Use a blocking access with this code pattern instead because a blocking access in this code pattern is more efficient in hardware than a nonblocking access in this code pattern.
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