tag: PIM

PDN Challenges In DRAM-Based Compute-In-Memory Systems (UT Austin)
By Technical Paper Link - 11 Apr, 2026 - Comments: 0

A new technical paper, "A comparative study on power delivery aspects of compute-in/near-memory approaches using DRAM," was published by researchers at UT Austin. Abstract "Compute-in-memory (PIM) mitigates the memory wall by performing computation within memory, reducing data movement and improving energy efficiency. DRAM-based PIM is particularly attractive due to its high density, matu... » read more

Data-Centric ML Compiler For PIM (U. of Toronto, Barcelona Supercomputing Center, ETH Zurich, Max Planck)
By Technical Paper Link - 19 Dec, 2025 - Comments: 0

A new technical paper titled "A Tensor Compiler for Processing-In-Memory Architectures" was published by researchers at University of Toronto, Barcelona Supercomputing Center, ETH Zurich, and the Max Planck Institute for Software Systems. Abstract "Processing-In-Memory (PIM) devices integrated with high-performance Host processors (e.g., GPUs) can accelerate memory-intensive kernels in Ma... » read more

Digital Memristor-Based PIM From A Device And Reliability View (Northwestern, Technion)
By Technical Paper Link - 25 Nov, 2025 - Comments: 0

A new technical paper titled "A Comparative Study of Digital Memristor-Based Processing-In-Memory from a Device and Reliability Perspective" was published by researchers at Northwestern University and  Technion – Israel Institute of Technology. Abstract "As data-intensive applications increasingly strain conventional computing systems, processing-in-memory (PIM) has emerged as a promis... » read more

AI Memory: Enabling The Next Era Of High-Performance Computing
By Tadashi Oda - 11 Nov, 2025 - Comments: 0

The rapid advancement of artificial intelligence (AI) is driving unprecedented demand for high-performance memory solutions. AI-driven applications are fueling significant year-over-year growth in high-bandwidth memory (HBM). However, as AI models grow in complexity—from large language models (LLMs) to real-time inference applications—the need for faster, higher-bandwidth, and energy-effici... » read more

Analog IMC Attention Mechanism For Fast And Energy-Efficient LLMs (FZJ, RWTH Aachen)
By Technical Paper Link - 15 Sep, 2025 - Comments: 0

A new technical paper titled "Analog in-memory computing attention mechanism for fast and energy-efficient large language models" was published by researchers at Forschungszentrum Jülich and RWTH Aachen. Abstract "Transformer networks, driven by self-attention, are central to large language models. In generative transformers, self-attention uses cache memory to store token projec... » read more

Tools, Models and System Support for PIM Architectures, With DRAM-Focus (ETH Zurich)
By Technical Paper Link - 04 Sep, 2025 - Comments: 0

A new technical paper titled "New Tools, Programming Models, and System Support for Processing-in-Memory Architectures" was published by researchers at ETH Zurich. Abstract "Our goal in this dissertation is to provide tools, programming models, and system support for PIM architectures (with a focus on DRAM-based solutions), to ease the adoption of PIM in current and future systems. To this ... » read more

Thermally-Aware, Multi-Objective Scheduling Framework for DL Workloads on Heterogeneous Multi-Chiplet PIM Architectures (UW–Madison, Washington State)
By Technical Paper Link - 19 Aug, 2025 - Comments: 0

A new technical paper titled "THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures" was published by researchers at the University of Wisconsin–Madison and Washington State University. Abstract "Chiplet-based integration enables large-scale systems that combine diverse technologies, enabling higher yield, lower costs, and sca... » read more

Energy-Efficient DRAM↔PIM Transfers for PIM Systems (KAIST)
By Technical Paper Link - 18 Sep, 2024 - Comments: 0

A new technical paper titled "PIM-MMU: A Memory Management Unit for Accelerating Data Transfers in Commercial PIM Systems" was published by researchers at KAIST. Abstract "Processing-in-memory (PIM) has emerged as a promising solution for accelerating memory-intensive workloads as they provide high memory bandwidth to the processing units. This approach has drawn attention not only from the... » read more

Survey of Energy Efficient PIM Processors
By Technical Paper Link - 01 Aug, 2024 - Comments: 0

A new technical paper titled "Survey of Deep Learning Accelerators for Edge and Emerging Computing" was published by researchers at University of Dayton and the Air Force Research Laboratory. Abstract "The unprecedented progress in artificial intelligence (AI), particularly in deep learning algorithms with ubiquitous internet connected smart devices, has created a high demand for AI compu... » read more

Increasing AI Energy Efficiency With Compute In Memory
By Katherine Derbyshire - 16 Nov, 2023 - Comments: 0

Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more than a science project. CIM solves two problems. First, it takes more energy to move data back and forth between memory and processor than to actually process it. And second, there is so much da... » read more

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