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Processing-using-memory (PuM) techniques leverage the analog operation ofmemory cells to perform computation. Several recent works have demonstrated PuMtechniques in off-the-shelf DRAM devices. Since DRAM is the dominant memorytechnology as main memory in current computing systems, these PuM techniquesrepresent an opportunity for alleviating the data movement bottleneck at verylow cost. However, system integration of PuM techniques imposes non-trivialchallenges that are yet to be solved. Design space exploration of potentialsolutions to the PuM integration challenges requires appropriate tools todevelop necessary hardware and software components. Unfortunately, currentspecialized DRAM-testing platforms, or system simulators do not provide theflexibility and/or the holistic system view that is necessary to deal with PuMintegration challenges.  We design and develop PiDRAM, the first flexible end-to-end framework thatenables system integration studies and evaluation of real PuM techniques.PiDRAM provides software and hardware components to rapidly integrate PuMtechniques across the whole system software and hardware stack (e.g., necessarymodifications in the operating system, memory controller). We implement PiDRAMon an FPGA-based platform along with an open-source RISC-V system. UsingPiDRAM, we implement and evaluate two state-of-the-art PuM techniques: in-DRAM(i) copy and initialization, (ii) true random number generation. Our resultsshow that the in-memory copy and initialization techniques can improve theperformance of bulk copy operations by 12.6x and bulk initialization operationsby 14.6x on a real system. Implementing the true random number generatorrequires only 190 lines of Verilog and 74 lines of C code using PiDRAM'ssoftware and hardware components.

PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAM