AutoAccel: Automated Accelerator Generation and Optimization with Composable, Parallel and Pipeline Architecture

CPU-FPGA heterogeneous architectures are attracting ever-increasing attention in an attempt to advance computational capabilities and energy efficiency in today's datacenters. These architectures provide programmers with the ability to reprogram the FPGAs for flexible acceleration of many workloads. Nonetheless, this advantage is often overshadowed by the poor programmability of FPGAs whose programming is conventionally a RTL design practice. Although recent advances in high-level synthesis (HLS) significantly improve the FPGA programmability, it still leaves programmers facing the challenge of identifying the optimal design configuration in a tremendous design space. This paper aims to address this challenge and pave the path from software programs towards high-quality FPGA accelerators. Specifically, we first propose the composable, parallel and pipeline (CPP) microarchitecture as a template of accelerator designs. Such a well-defined template is able to support efficient accelerator designs for a broad class of computation kernels, and more importantly, drastically reduce the design space. Also, we introduce an analytical model to capture the performance and resource trade-offs among different design configurations of the CPP microarchitecture, which lays the foundation for fast design space exploration. On top of the CPP microarchitecture and its analytical model, we develop the AutoAccel framework to make the entire accelerator generation automated. AutoAccel accepts a software program as an input and performs a series of code transformations based on the result of the analytical-model-based design space exploration to construct the desired CPP microarchitecture. Our experiments show that the AutoAccel-generated accelerators outperform their corresponding software implementations by an average of 72x for a broad class of computation kernels

Efficient Implementation on Low-Cost SoC-FPGAs of TLSv1.2 Protocol with ECC_AES Support for Secure IoT Coordinators

Security management for IoT applications is a critical research field, especially when taking into account the performance variation over the very different IoT devices. In this paper, we present high-performance client/server coordinators on low-cost SoC-FPGA devices for secure IoT data collection. Security is ensured by using the Transport Layer Security (TLS) protocol based on the TLS_ECDHE_ECDSA_WITH_AES_128_CBC_SHA256 cipher suite. The hardware architecture of the proposed coordinators is based on SW/HW co-design, implementing within the hardware accelerator core Elliptic Curve Scalar Multiplication (ECSM), which is the core operation of Elliptic Curve Cryptosystems (ECC). Meanwhile, the control of the overall TLS scheme is performed in software by an ARM Cortex-A9 microprocessor. In fact, the implementation of the ECC accelerator core around an ARM microprocessor allows not only the improvement of ECSM execution but also the performance enhancement of the overall cryptosystem. The integration of the ARM processor enables to exploit the possibility of embedded Linux features for high system flexibility. As a result, the proposed ECC accelerator requires limited area, with only 3395 LUTs on the Zynq device used to perform high-speed, 233-bit ECSMs in 413 µs, with a 50 MHz clock. Moreover, the generation of a 384-bit TLS handshake secret key between client and server coordinators requires 67.5 ms on a low cost Zynq 7Z007S device

High throughput FPGA Implementation of Advanced Encryption Standard Algorithm

 The growth of computer systems and electronic communications and transactions has meant that the need for effective security and reliability of data communication, processing and storage is more important than ever. In this context, cryptography is a high priority research area in engineering. The Advanced Encryption Standard (AES) is a symmetric-key criptographic algorithm for protecting sensitive information and is one of the most widely secure and used algorithm today. High-throughput, low power and compactness have always been topic of interest for implementing this type of algorithm. In this paper, we are interested on the development of high throughput architecture and implementation of AES algorithm, using the least amount of hardware possible. We have adopted a pipeline approach in order to reduce the critical path and achieve competitive performances in terms of throughput and efficiency. This approach is effectively tested on the AES S-Box substitution. The latter is a complex transformation and the key point to improve architecture performances. Considering the high delay and hardware required for this transformation, we proposed 7-stage pipelined S-box by using composite field in order to deal with the critical path and the occupied area resources. In addition, efficient AES key expansion architecture suitable for our proposed pipelined AES is presented. The implementation had been successfully done on Virtex-5 XC5VLX85 and Virtex-6 XC6VLX75T Field Programmable Gate Array (FPGA) devices using Xilinx ISE v14.7. Our AES design achieved a data encryption rate of 108.69 Gbps and used only 6361 slices ressource. Compared to the best previous work, this implementation improves data throughput by 5.6% and reduces the used slices to 77.69%