Explore the intricate structure of the DRAM subsystem, including memory channels, DIMMs, ranks, chips, banks, and rows/columns. Delve into the breakdown of DIMMs, ranks, chips, and banks to comprehend the design and functioning of DRAM memory systems. Gain insights into address decoding, row/column

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Graph-based data science offers a powerful approach to analyzing data by leveraging graph structures. This involves using graph representation, analysis algorithms, ML/AI techniques, kernels, embeddings, and neural networks. Real-world examples show the utility of data graphs in various domains like

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In this informative presentation, Moinuddin Qureshi discusses the risk management aspects and background of Row-Hammer vulnerabilities in DRAM, proposing new defenses and emphasizing the importance of detecting and addressing unknown threats. The proposal suggests rethinking ECC designs to enhance d

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Utilizing machine learning to forecast path-based slack in graph-based timing analysis offers a solution for optimizing power and area efficiency in the design process. The Static Timing Analysis incorporates accurate path-based analysis (PBA) and fast graph-based analysis (GBA) to estimate transiti

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Recommender systems play a crucial role in providing personalized recommendations to users. This article delves into various types of recommender systems including Collaborative Filtering, Content-Based, Knowledge-Based, and Group Recommender Systems. Collaborative Filtering involves making predicti

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In the field of computer architecture, SRAM and DRAM are two prevalent memory technologies with distinct characteristics. SRAM retains data as long as power is present, while DRAM is dynamic and requires data refreshing. SRAM is built with high-speed CMOS technology, whereas DRAM is more dense and b

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Cache memory is a crucial component in computer architecture that aims to accelerate memory accesses by storing frequently used data closer to the CPU. This faster access is achieved through SRAM-based cache, which offers much shorter cycle times compared to DRAM. Various cache mapping schemes are e

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DRAM-based QUAC-TRNG provides high-throughput and low-latency true random number generation by utilizing commodity DRAM devices. By employing Quadruple Row Activation (QUAC), this method outperforms existing TRNGs, achieving a 15.08x improvement in throughput and passing all 15 NIST randomness tests

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SIMDRAM introduces a novel framework for efficient computation in DRAM, aiming to overcome data movement bottlenecks. It emphasizes Processing-in-Memory (PIM) and Processing-using-Memory (PuM) paradigms to enhance processing capabilities within DRAM while minimizing architectural changes. The motiva

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Detailed experimental study reveals that DRAM power models may not provide accurate insights into power consumption. The increasing importance of managing DRAM power in system design is emphasized. The study delves into DRAM organization, operation, and power consumption patterns, highlighting the n

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Understanding the liabilities and responsibilities of bar and tavern owners under the Dram Shop Act based on the case of Build It and They Will Drink, Inc. v. Strauch. The act outlines exceptions where licensees can be held civilly liable for selling alcohol to minors or visibly intoxicated individu

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Limited DRAM bandwidth poses a critical bottleneck in GPU performance, necessitating a comprehensive scheduling policy to reduce cache miss rates, enhance DRAM bandwidth, and improve latency hiding for GPUs. The CTA-aware scheduling techniques presented address these challenges by optimizing resourc

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Exploring the integration of Coherent DRAM Caches in multi-node systems to improve memory performance. Discusses the benefits, challenges, and potential performance improvements compared to existing memory-side cache solutions.

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Explore the challenges faced by Moore's Law in relation to bandwidth limitations and the innovative solutions such as 3D-DRAM caches and compressed memory systems. Discover how compressing DRAM caches can improve bandwidth and capacity, leading to enhanced performance in memory-intensive application

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Skeena presents efficient and consistent cross-engine transactions, offering solutions to challenges faced by traditional database engines. By utilizing memory-optimized database engines and a multi-engine DBMS approach, Skeena addresses issues such as high costs and compatibility concerns associate

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This study investigates the effectiveness of GUI-based assignments compared to text-based assignments in a CS1 course. The research explores how student motivation impacts their performance and retention in the course. It also delves into student preferences between GUI-based and text-based assignme

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Explore how ThyNVM enables software-transparent crash consistency in persistent memory systems, overcoming challenges and offering a new hardware-based checkpointing mechanism that adapts to DRAM and NVM characteristics while reducing latency and overhead.

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Addressing fundamental latency trade-offs in designing DRAM caches involves considerations such as memory stacking for improved latency and bandwidth, organizing large caches at cache-line granularity to minimize wasted space, and optimizing cache designs to reduce access latency. Challenges include

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Demonstrating and analyzing RowPress, a novel read disturbance phenomenon causing bitflips in DRAM chips. Different from RowHammer vulnerability, RowPress showcases effective solutions on real Intel systems with DRAM chips.

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Addressing memory latency challenges in irregular GPGPU applications, this study explores techniques like warp-aware memory scheduling and GPU memory controller optimization to reduce DRAM latency divergence. The research delves into the impact of SIMD lanes, coalescers, and warp-aware scheduling on

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Despite extensive research, DRAM remains vulnerable to Rowhammer attacks. The Panopticon project proposes a novel in-DRAM mitigation technique using counter mats within DRAM devices. This approach does not require costly changes at multiple layers and leverages existing DRAM logic for efficient miti

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Exploring the nature of DRAM errors, this study delves into the causes, types, and implications for system design. From soft errors caused by cosmic rays to hard errors due to permanent hardware issues, the research examines error protection mechanisms and open questions surrounding DRAM errors. Pre

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Explore the innovative use of stacked DRAM as Part of Memory (PoM) to increase overall memory capacity and eliminate duplication. The system involves OS-managed PoM, challenges, and the potential of hardware-managed PoM to reduce OS-related overhead. Learn about the practical implications and evalua

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The evolution of memory scaling poses challenges for system performance growth due to limitations in memory hierarchy, capacity gaps, and DRAM scaling obstacles. The need for alternative technologies and architectural support to address these challenges is highlighted, focusing on reducing latency,

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This research delves into the complexities of latency variation in modern DRAM chips, highlighting factors such as imperfect manufacturing processes and high standard latencies chosen to boost yield. The study aims to characterize latency variation, optimize DRAM performance, and develop mechanisms

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The Dirty-Block Index (DBI) is a solution to address inefficiencies in caches by removing dirty bits from cache tag stores, improving query response efficiency, and enabling various optimizations like DRAM-aware writeback. Its implementation leads to significant performance gains and cache area redu

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Efficiently coordinating off-chip read/write bandwidth through the Bandwidth-aware LLC proposal yields a 12% performance improvement in an 8-core system across multiple workloads. This approach optimizes DRAM read latency, surpassing existing policies and filling performance gaps while confirming lo

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MemC3 is a specialized key-value store that combines CLOCK and Concurrent Cuckoo Hashing to improve performance and efficiency. Memcached, an established DRAM-based key-value store, is also discussed along with its LRU eviction strategy. The use of internal chaining hashtable and LRU caching in Memc

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This collection of research delves into the power challenges faced by memory-intensive databases (MMDBs) and explores strategies for reducing DRAM power draw. Topics covered include the impact of hardware features on power consumption, experimental setups for analyzing power breakdown, and the effec

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Memory requests from different threads can cause interferences in DRAM banks, impacting performance. The solution proposed involves partitioning DRAM banks between threads to eliminate interferences, leading to improved performance and energy savings.

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Reduce average DRAM access latency by leveraging row access locality with ChargeCache, a cost-effective solution requiring no modifications to existing DRAM chips. By tracking recently accessed rows and adjusting timing parameters, ChargeCache achieves higher performance and lower DRAM energy consum

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Uncertainty Quantification (UQ) is crucial in determining likely outcomes in scenarios with unknown factors. Explore the concept through the Algae Example, where parameters like growth rates pose challenges due to uncertainty. Statistical techniques like MCMC and the DRAM algorithm play key roles in

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Efficiently managing DRAM caches is crucial due to increasing memory demands and bandwidth limitations. Strategies like using DRAM as a cache, architectural considerations for large DRAM caches, and understanding replacement policies are explored in this study to enhance memory bandwidth and capacit

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This research focuses on improving bulk data movement efficiency within DRAM by introducing Low-Cost Inter-Linked Subarrays (LISA). By providing wide connectivity between subarrays, LISA enables fast inter-subarray data transfers, reducing latency and energy consumption. Key applications include fas

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Explore the complexities of designing a memory system for computer architecture. Delve into the tradeoffs between area, power, and latency, considering the limitations of using only flip-flops, SRAM cells, or DRAM cells. Discover the challenges in creating an efficient memory system that balances st

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CLR-DRAM introduces a low-cost DRAM architecture that enables dynamic configuration for high capacity or low latency at the granularity of a row. By allowing a single DRAM row to switch between max-capacity and high-performance modes, it reduces key timing parameters, improves system performance, an

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Neural network accelerators are achieving high energy efficiency and performance for recognition and mining applications. To overcome memory bandwidth constraints, the proposal suggests mapping the entire CNN into SRAM and moving closer to sensors to minimize memory access for I/O. Placing the CNN a

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Different memory technologies present unique strengths, and a hybrid memory system combining DRAM and PCM aims to leverage the best of both worlds. This research explores the challenge of data placement between these diverse memory devices, highlighting the use of row buffer locality as a key criter

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Exploring the potential of Phase Change Memory (PCM) technology, this paper presents algorithm design for PCM-based main memory in the context of database systems. The emerging non-volatile memory technology of PCM is compared to DRAM, showcasing its byte-addressable nature, lower latency, and highe

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The BEER project explores how on-die ECC complicates DRAM reliability studies by concealing error characteristics. It aims to uncover the unique ECC function of DRAM chips and infer error locations in error-prone cells. The study highlights the challenges in identifying and correcting bit flips obfu

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