Intel® High Level Synthesis Compiler Pro Edition: Best Practices Guide

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ID 683152
Date 12/04/2023
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Document Table of Contents
Document Table of Contents x
1. Intel® HLS Compiler Pro Edition Best Practices Guide 2. Best Practices for Coding and Compiling Your Component 3. FPGA Concepts 4. Interface Best Practices 5. Loop Best Practices 6. fMAX Bottleneck Best Practices 7. Memory Architecture Best Practices 8. System of Tasks Best Practices 9. Datatype Best Practices 10. Advanced Troubleshooting A. Intel® HLS Compiler Pro Edition Best Practices Guide Archives B. Document Revision History for Intel® HLS Compiler Pro Edition Best Practices Guide
1. Intel® HLS Compiler Pro Edition Best Practices Guide x
1.1. Pending Deprecation of the Intel® HLS Compiler
3. FPGA Concepts x
3.1. FPGA Architecture Overview 3.2. Concepts of FPGA Hardware Design 3.3. Methods of Hardware Design
3.1. FPGA Architecture Overview x
3.1.1. Adaptive Logic Module (ALM) 3.1.2. Digital Signal Processing (DSP) Block 3.1.3. Random-Access Memory (RAM) Blocks
3.1.1. Adaptive Logic Module (ALM) x
3.1.1.1. Lookup Table (LUT) 3.1.1.2. Register
3.2. Concepts of FPGA Hardware Design x
3.2.1. Maximum Frequency (fMAX) 3.2.2. Latency 3.2.3. Pipelining 3.2.4. Throughput 3.2.5. Datapath 3.2.6. Control Path 3.2.7. Occupancy
3.3. Methods of Hardware Design x
3.3.1. How Source Code Becomes a Custom Hardware Datapath 3.3.2. Scheduling 3.3.3. Mapping Parallelism Models to FPGA Hardware 3.3.4. Memory Types
3.3.1. How Source Code Becomes a Custom Hardware Datapath x
3.3.1.1. Mapping Source Code Instructions to Hardware 3.3.1.2. Mapping Arrays and Their Accesses to Hardware
3.3.2. Scheduling x
3.3.2.1. Dynamic Scheduling 3.3.2.2. Clustering the Datapath 3.3.2.3. Handshaking Between Clusters
3.3.3. Mapping Parallelism Models to FPGA Hardware x
3.3.3.1. Data Parallelism 3.3.3.2. Task Parallelism
3.3.3.1. Data Parallelism x
3.3.3.1.1. Executing Independent Operations Simultaneously 3.3.3.1.2. Pipelining
3.3.3.1.2. Pipelining x
3.3.3.1.2.1. Pipelining Loops Within A Component 3.3.3.1.2.2. Pipelining Across Component Invocations
3.3.4. Memory Types x
3.3.4.1. Component Memory 3.3.4.2. External Memory
4. Interface Best Practices x
4.1. Choose the Right Interface for Your Component 4.2. Control LSUs For Your Variable-Latency MM Host Interfaces 4.3. Avoid Pointer Aliasing
4.1. Choose the Right Interface for Your Component x
4.1.1. Pointer Interfaces 4.1.2. Avalon® Memory Mapped Host Interfaces 4.1.3. Avalon® Memory Mapped Agent Memories 4.1.4. Avalon® Memory Mapped Agent Registers 4.1.5. Avalon® Streaming Interfaces 4.1.6. Pass-by-Value Interface
5. Loop Best Practices x
5.1. Reuse Hardware By Calling It In a Loop 5.2. Parallelize Loops 5.3. Construct Well-Formed Loops 5.4. Minimize Loop-Carried Dependencies 5.5. Avoid Complex Loop-Exit Conditions 5.6. Convert Nested Loops into a Single Loop 5.7. Place if-Statements in the Lowest Possible Scope in a Loop Nest 5.8. Declare Variables in the Deepest Scope Possible 5.9. Raise Loop II to Increase fMAX 5.10. Control Loop Interleaving
5.2. Parallelize Loops x
5.2.1. Pipeline Loops 5.2.2. Unroll Loops 5.2.3. Example: Loop Pipelining and Unrolling
6. fMAX Bottleneck Best Practices x
6.1. Balancing Target fMAX and Target II
7. Memory Architecture Best Practices x
7.1. Example: Overriding a Coalesced Memory Architecture 7.2. Example: Overriding a Banked Memory Architecture 7.3. Merge Memories to Reduce Area 7.4. Example: Specifying Bank-Selection Bits for Local Memory Addresses
7.3. Merge Memories to Reduce Area x
7.3.1. Example: Merging Memories Depth-Wise 7.3.2. Example: Merging Memories Width-Wise
8. System of Tasks Best Practices x
8.1. Executing Multiple Loops in Parallel 8.2. Sharing an Expensive Compute Block 8.3. Implementing a Hierarchical Design 8.4. Balancing Capacity in a System of Tasks
8.4. Balancing Capacity in a System of Tasks x
8.4.1. Enable the Intel® HLS Compiler to Infer Data Path Buffer Capacity Requirements 8.4.2. Explicitly Add Buffer Capacity to Your Design When Needed
9. Datatype Best Practices x
9.1. Avoid Implicit Data Type Conversions 9.2. Avoid Negative Bit Shifts When Using the ac_int Datatype
10. Advanced Troubleshooting x
10.1. Component Fails Only In Simulation 10.2. Component Gets Poor Quality of Results
1. Intel® HLS Compiler Pro Edition Best Practices Guide
2. Best Practices for Coding and Compiling Your Component
3. FPGA Concepts
4. Interface Best Practices
5. Loop Best Practices
6. fMAX Bottleneck Best Practices
7. Memory Architecture Best Practices
8. System of Tasks Best Practices
9. Datatype Best Practices
10. Advanced Troubleshooting
A. Intel® HLS Compiler Pro Edition Best Practices Guide Archives
B. Document Revision History for Intel® HLS Compiler Pro Edition Best Practices Guide

4.1.1. Pointer Interfaces

Software developers accustomed to writing code that targets a CPU might first try to code this algorithm by declaring vectors a, b, and c as pointers to get the data in and out of the component.
Using pointers in this way results in a single Avalon Memory-Mapped (MM) Host interface that the three input variables share.

Pointers in a component are implemented as Avalon® Memory Mapped ( Avalon® -MM) host interfaces with default settings. For more details about pointer parameter interfaces, see Intel HLS Compiler Default Interfaces in Intel® High Level Synthesis Compiler Pro Edition Reference Manual.

The vector addition component example with pointer interfaces can be coded as follows: 
component void vector_add(int* a,
                          int* b,
                          int* c,
                          int N) {
  #pragma unroll 8
  for (int i = 0; i < N; ++i) {
    c[i] = a[i] + b[i];
  }
}
The following diagram shows the Function View in the Graph Viewer that is generated when you compile this example. Because the loop is unrolled by a factor of 8, the diagram shows that vector_add.B2 has 8 loads for vector a, 8 loads for vector b, and 8 stores for vector c. In addition, all of the loads and stores are arbitrated on the same memory, resulting in inefficient memory accesses.
Figure 24. Graph Viewer Function View for vector_add Component with Pointer Interfaces


The following Loop Analysis report shows that the component has an undesirably high loop initiation interval (II). The II is high because vectors a, b, and c are all accessed through the same Avalon-MM Host interface. The Intel® HLS Compiler Pro Edition uses stallable arbitration logic to schedule these accesses, which results in poor performance and high FPGA area use.

In addition, the compiler cannot assume there are no data dependencies between loop iterations because pointer aliasing might exist. The compiler cannot determine that vectors a, b, and c do not overlap. If data dependencies exist, the Intel® HLS Compiler cannot pipeline the loop iterations effectively.



Compiling the component with an Intel® Quartus® Prime compilation flow targeting an Intel® Arria® 10 device results in the following QoR metrics, including high ALM usage, high latency, high II, and low fMAX. All of which are undesirable properties in a component.
Table 2.  QoR Metrics for a Component with a Pointer Interface1
QoR Metric Value
ALMs 15593.5
DSPs 0
RAMs 30
fMAX (MHz)2 298.6
Latency (cycles) 24071
Initiation Interval (II) (cycles) ~508
1The compilation flow used to calculate the QoR metrics used Intel® Quartus® Prime Pro Edition Version 17.1.
2The fMAX measurement was calculated from a single seed.
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