In-FPGA Instrumentation Framework for OpenCL-Based Designs

Abstract

The productivity achieved when developing applications on high-performance reconfigurable heterogeneous computing (HPRHC) systems is increased by using the Open Computing Language (OpenCL). However, the hardware produced by OpenCL compilers in field-programmable gate arrays (FPGAs) can result in severe performance bottlenecks that are challenging to solve. The problem is compounded by the fact that the generated netlist details are disorganized, making them mostly unreadable and only partially visible to designers. This paper proposes an in-FPGA instrumentation method and a new framework for extracting the FPGA-cycle-accurate timing performances of OpenCL-based designs. The results clearly show that the chosen execution model for OpenCL-based designs strongly affects the timing performance when it is not properly implemented. Our framework is implemented on an HPRHC platform that contains a CPU and two Arria10 FPGAs, and it is evaluated with a wide variety of benchmarks with different complexities. After testing on the reported benchmarks, the average logic overhead for one inserted instrument is 0.2 % of the total amount of adaptive look-up tables (ALUTs) and 0.1 % of the total registers in an FPGA. This resource utilization is between 1.5 and six times lower than those reported in the best previously published works. The scalability of the framework is also evaluated by inserting up to 50 instruments. The experimental results show that the average logic utilization per instrument is 0.19 % of the ALUTs and 0.17 % of the registers in the FPGA when 50 instruments are inserted.

Acceleration of the Secure Hash Algorithm-256 (SHA-256) on an FPGA-CPU Cluster Using OpenCL

“…Second, 64 hashing rounds are performed on each 512-bit message block for generating 64 words (W) with a size of 32 bits each (lines 4-7). [13][14][15]. The final digest message Hash is then generated and stored in global memory as shown in line 17 (Fig.…”

“…Thus, OpenCL-based optimization techniques are required to achieve good performance. A solution that offers great potential to optimize OpenCL-based designs is identifying performance bottlenecks by inserting embedded monitors [14,15]. This paper explores and evaluates several OpenCL-based FPGA implementations of SHA-256.…”