What it is

Processor-in-Memory (PIM) is an emerging computing architecture that integrates processing capabilities directly within memory modules, reducing the need to move data back and forth between the CPU and memory. Traditional architectures suffer from the “memory wall”, where data transfer latency and bandwidth limitations dominate system performance. PIM mitigates this by performing computations near or inside memory arrays, improving throughput, energy efficiency, and latency.

PIM technologies combine hardware design, memory technology (DRAM, SRAM, non-volatile memory), and system-level architecture to accelerate data-intensive tasks. Applications range from AI model training and inference to real-time analytics and large-scale scientific simulations.

Applications

• AI model inference and training: Faster neural network computations, matrix multiplications, and attention mechanisms.
• Real-time analytics: In-memory processing of large-scale transaction or sensor data for near-instant decision-making.
• Scientific computing & simulations: High-performance physics simulations, weather modeling, and genomic data analysis.
• Graph processing & database acceleration: Social network analysis, recommendation systems, and big data queries.
• Edge computing: Low-power PIM modules for AI in IoT devices and autonomous systems.
• Cloud infrastructure: Integration into servers to reduce memory bottlenecks in hyperscale data centers.

Future potential

1. Standard in next-gen data centers: PIM-enabled servers becoming mainstream for AI and analytics workloads.
2. Heterogeneous integration: Combining PIM with GPUs, TPUs, and neuromorphic cores for hybrid accelerators.
3. Non-volatile memory PIM: Using emerging NVM technologies like ReRAM or PCM for persistent, in-memory computation.
4. AI-driven architecture optimization: Machine learning algorithms for dynamic allocation of in-memory computations.
5. Processor-less computing nodes: Future architectures may rely on entirely in-memory computation for specific workloads.
6. Energy-aware computing: PIM as a cornerstone for sustainable AI and exascale computing platforms.

Current Research Areas in Processor-in-Memory (PIM) Technology

1. Memory-embedded processing units: Design and fabrication of DRAM, SRAM, and NVM with integrated compute logic.
2. Data-intensive AI acceleration: Algorithms optimized for in-memory execution (matrix multiplication, CNN, transformers).
3. Energy-efficient architectures: Low-power design techniques for large-scale PIM deployment.
4. Non-volatile PIM technologies: Exploring ReRAM, PCM, MRAM, and other emerging memory types for computation.
5. Hardware-software co-design: Compiler and runtime support for efficient utilization of PIM architectures.
6. Hybrid memory systems: Integration of PIM with traditional CPU/GPU/TPU pipelines for heterogeneous computing.
7. Reliability and fault-tolerance: Mitigating errors due to high-density memory processing.
8. Security in PIM systems: Protecting in-memory computations against side-channel and data-leakage attacks.
9. Graph and database acceleration: Optimized in-memory algorithms for large-scale graph processing.
10. Benchmarking and simulation: Developing metrics and simulators for evaluating PIM performance and energy efficiency.
11. Emerging device-level innovations: Memristor-based logic-in-memory, stochastic computing, and analog PIM techniques.

Key Journals Accepting Papers on Processor-in-Memory (PIM) Technology

Below are selected Open Access, Hybrid, and Subscription journals indexed in Scopus and recognized by CSI Tools for publishing PIM research.

Open Access Journals

1. IEEE Access
   Focus: Broad coverage of computing, electronics, memory, and AI acceleration.
   Fit: PIM architectures, hardware-software co-design, and emerging memory devices.
   Indexing: Scopus Q1–Q2, CSI-recognized.
2. Frontiers in Computer Science
   Focus: Computer architecture, AI hardware, and memory systems.
   Fit: Design and evaluation of PIM-enabled systems for AI and big data.
   Indexing: Scopus Q2–Q3, CSI-approved.
3. Microelectronics Journal (Open Access option)
   Focus: Hardware, memory, and semiconductor technologies.
   Fit: Device-level PIM research and integration in CMOS or emerging technologies.
   Indexing: Scopus Q2–Q3, CSI-recognized.

Hybrid Journals

1. IEEE Transactions on Computers
   Focus: Computer architecture, processing-in-memory, and heterogeneous computing.
   Fit: Architectural innovations, simulation studies, and PIM-based AI accelerators.
   Indexing: Scopus Q1, widely used in CSI rankings.
2. ACM Transactions on Embedded Computing Systems (TECS)
   Focus: Embedded systems, memory-compute integration, and low-power design.
   Fit: PIM for edge devices, IoT, and low-energy AI.
   Indexing: Scopus Q1, CSI-evaluated.
3. Journal of Parallel and Distributed Computing (JPDC)
   Focus: Distributed computing, memory hierarchy, and high-performance architectures.
   Fit: PIM in large-scale simulations and cloud/cluster architectures.
   Indexing: Scopus Q1, CSI-recognized.
4. IEEE Transactions on Very Large Scale Integration Systems (TVLSI)
   Focus: Hardware and architecture for VLSI and memory systems.
   Fit: PIM chip design, reliability, and emerging memory technologies.
   Indexing: Scopus Q1, CSI-evaluated.

Subscription Journals

1. ACM Journal on Emerging Technologies in Computing Systems (JETC)
   Focus: Innovative computing paradigms, including in-memory computing.
   Fit: Conceptual and experimental PIM systems for AI acceleration.
   Indexing: Scopus Q1, CSI-recognized.
2. IEEE Transactions on Computers and IEEE Micro
   Focus: Computer architecture, memory hierarchy, and processor innovations.
   Fit: System-level PIM studies, hybrid CPU/PIM architectures.
   Indexing: Scopus Q1, CSI-evaluated.
3. Integration, the VLSI Journal (Elsevier)
   Focus: VLSI system design, memory-integration, and semiconductor innovations.
   Fit: Device-level and chip-level PIM architecture publications.
   Indexing: Scopus Q2–Q1, CSI-recognized.
4. Journal of Systems Architecture (JSA)
   Focus: Hardware-software co-design and computer architecture.
   Fit: PIM system integration, benchmarking, and real-world applications.
   Indexing: Scopus Q2–Q1, CSI-evaluated.

Summary Table — Processor-in-Memory (PIM) Journals Overview

Type	Journal Name	Focus Area	Scopus Indexed	CSI Recognized
Open Access	IEEE Access	Computing & memory systems	✅	✅
Open Access	Frontiers in Computer Science	Architecture & AI hardware	✅	✅
Open Access	Microelectronics Journal	Device-level PIM	✅	✅
Hybrid	IEEE Trans. on Computers	Architecture & PIM	✅	✅
Hybrid	ACM TECS	Embedded & low-power systems	✅	✅
Hybrid	JPDC	Parallel & distributed computing	✅	✅
Hybrid	IEEE TVLSI	VLSI & memory integration	✅	✅
Subscription	ACM JETC	Emerging computing paradigms	✅	✅
Subscription	IEEE Micro	Processor & memory innovations	✅	✅
Subscription	Integration, the VLSI Journal	Chip-level PIM design	✅	✅
Subscription	Journal of Systems Architecture	System-level PIM & benchmarking	✅	✅