Tassadaq Hussain

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One of the main challenges in the design of hardware accelerators is the efficient access of data from the external memory. Improving and optimizing the functionality of the memory controller between the external memory and the accelerators is therefore critical. In this paper, we advance toward this goal by proposing PPMC, the Programmable Pattern-based(More)
— A generic multi-accelerator system comprises a microprocessor unit that schedules the accelerators along with the necessary data movements. The system, having the processor as control unit, encounters multiple delays (memory and task management) which degrade the overall system performance. This performance degradation demands an efficient memory manager(More)
—Reconfigurable computers have started to appear in the HPC landscape, albeit at a slow pace. Adoption is still being hindered by the design methodologies and slow implementation cycles. Recently, methodologies based on High Level Synthesis (HLS) have begun to flourish and the reconfigurable supercom-puting community is slowly adopting these techniques. In(More)
—The ever-increasing complexity of high-performance computing applications limits performance due to memory constraints in FPGAs. To address this issue, we propose the Advanced Pattern based Memory Controller (APMC), which supports both regular and irregular memory patterns. The proposed memory controller systematically reduces the latency faced by(More)
—In this work, we propose a Programmable Vector Memory Controller (PVMC), which boosts noncontiguous vector data accesses by integrating descriptors of memory patterns, a specialized local memory, a memory manager in hardware, and multiple DRAM controllers. We implemented and validated the proposed system on an Altera DE4 FPGA board. We compare the(More)
• In this article, we propose PMSS a Programmable Memory System and Scheduler. • The PMSS can operates without intervention of master core or Operating system. • It schedules multi-accelerators and manages their memory access patterns. • The system is evaluated with memory intensive accelerators tested on a Xilinx ML505 evaluation FPGA board. • Results show(More)