Publications

2024

1. ACM TACO

   Sectored DRAM: An Energy-Efficient High-Throughput and Practical Fine-Grained DRAM Architecture

   Ataberk Olgun, Nisa Bostanci, Geraldo F. Oliveira, Yahya Can Tugrul, Rahul Bera, A. Giray Yaglikci, Hasan Hassan, Oguz Ergin, and Onur Mutlu

   ACM TACO, 2024

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   There are two major sources of inefficiency in computing systems that use modern DRAM devices as main memory. First, due to coarse-grained data transfers (size of a cache block, usually 64B between the DRAM and the memory controller, systems waste energy on transferring data that is not used. Second, due to coarse-grained DRAM row activation, systems waste energy by activating DRAM cells that are unused in many workloads where spatial locality is lower than the large row size (usually 8-16KB). We propose Sectored DRAM, a new, low-overhead DRAM substrate that alleviates the two inefficiencies, by enabling fine-grained DRAM access and activation. To efficiently retrieve only the useful data from DRAM, Sectored DRAM exploits the observation that many cache blocks are not fully utilized in many workloads due to poor spatial locality. Sectored DRAM predicts the words in a cache block that will likely be accessed during the cache block’s cache residency and: (i) transfers only the predicted words on the memory channel, as opposed to transferring the entire cache block, by dynamically tailoring the DRAM data transfer size for the workload and (ii) activates a smaller set of cells that contain the predicted words, as opposed to activating the entire DRAM row, by carefully operating physically isolated portions of DRAM rows (MATs). Compared to prior work in fine-grained DRAM, Sectored DRAM greatly reduces DRAM energy consumption, does not reduce DRAM throughput, and can be implemented with low hardware cost. We evaluate Sectored DRAM using 41 workloads from widely-used benchmark suites. Sectored DRAM reduces the DRAM energy consumption of highly-memory-intensive workloads by up to (on average) 33% (20%) while improving their performance by 17% on average. Sectored DRAM’s DRAM energy savings, combined with its system performance improvement, allows system-wide energy savings of up to 23%.

   @article{olgun2024sectored,
     title = {{Sectored DRAM: An Energy-Efficient High-Throughput and Practical Fine-Grained DRAM Architecture}},
     author = {Olgun, Ataberk and Bostanci, Nisa and Oliveira, Geraldo F. and Tugrul, Yahya Can and Bera, Rahul and Yaglikci, A. Giray and Hassan, Hasan and Ergin, Oguz and Mutlu, Onur},
     journal = {ACM TACO},
     year = {2024},
   }

2. USENIX Security

   ABACuS: All-Bank Activation Counters for Scalable and Low Overhead RowHammer Mitigation

   Ataberk Olgun, Yahya Can Tugrul, Nisa Bostanci, Ismail Emir Yuksel, Haocong Luo, Steve Rhyner, Abdullah Giray Yaglikci, Geraldo F. Oliveira, and Onur Mutlu

   In USENIX Security, 2024

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   We introduce ABACuS, a new low-cost hardware-counter-based RowHammer mitigation technique that performance-, energy-, and area-efficiently scales with worsening RowHammer vulnerability. We observe that both benign workloads and RowHammer attacks tend to access DRAM rows with the same row address in multiple DRAM banks at around the same time. Based on this observation, ABACuS’s key idea is to use a single shared row activation counter to track activations to the rows with the same row address in all DRAM banks. Unlike state-of-the-art RowHammer mitigation mechanisms that implement a separate row activation counter for each DRAM bank, ABACuS implements fewer counters (e.g., only one) to track an equal number of aggressor rows. Our evaluations show that ABACuS securely prevents RowHammer bitflips at low performance/energy overhead and low area cost. We compare ABACuS to four state-of-the-art mitigation mechanisms. At a near-future RowHammer threshold of 1000, ABACuS incurs only 0.58% (0.77%) performance and 1.66% (2.12%) DRAM energy overheads, averaged across 62 single-core (8-core) workloads, requiring only 9.47 KiB of storage per DRAM rank. At the RowHammer threshold of 1000, the best prior low-area-cost mitigation mechanism incurs 1.80% higher average performance overhead than ABACuS, while ABACuS requires 2.50X smaller chip area to implement. At a future RowHammer threshold of 125, ABACuS performs very similarly to (within 0.38% of the performance of) the best prior performance- and energy-efficient RowHammer mitigation mechanism while requiring 22.72X smaller chip area.

   @inproceedings{olgun2024abacus,
     title = {{ABACuS: All-Bank Activation Counters for Scalable and Low Overhead RowHammer Mitigation}},
     author = {Olgun, Ataberk and Tugrul, Yahya Can and Bostanci, Nisa and Yuksel, Ismail Emir and Luo, Haocong and Rhyner, Steve and Yaglikci, Abdullah Giray and Oliveira, Geraldo F. and Mutlu, Onur},
     booktitle = {USENIX Security},
     year = {2024}
   }

3. HPCA

   MIMDRAM: An End-to-End Processing-using-DRAM System for Energy-Efficient and Programmer-Transparent MIMD Computing

   Geraldo F. Oliveira, Ataberk Olgun, Giray Yaglikci, Nisa Bostanci, Juan Gomez Luna, Saugata Ghose, and Onur Mutlu

   In HPCA, 2024

   Abs

   Processing-using-DRAM (PuD) is a processing-in-memory (PIM) approach that uses DRAM’s massive parallelism to execute ultra-wide SIMD operations. However, DRAM rows’ large and rigid granularity limits the effectiveness and applicability of PuD in three ways. First, since applications display varying degrees of SIMD parallelism, PuD execution frequently leads to underutilization, throughput loss, and energy waste. Second, due to a lack of interconnecting networks that connect columns in a DRAM array, most PuD architectures are limited to the execution of map operations. Third, due to the lack of compiler support for PuD, users need to manually extract SIMD parallelism from an application and map computation to the underlying hardware. Our goal is to design a flexible PuD system that overcomes the limitations caused by the large and rigid granularity of PuD. To do so, we propose MIMDRAM, a hardware/software co-designed PuD system that introduces new mechanisms to allocate and control only the needed computing resources for PuD computation. The key idea of MIMDRAM is to leverage fine- grained DRAM (i.e., the ability to access portions of a DRAM row) for PuD. By exploiting this key idea, MIMDRAM enables a MIMD execution model on a single DRAM array (and SIMD execution within each segment). On the hardware side, MIMDRAM does simple changes to (i) DRAM’s row access circuitry to enable concurrent execution of PuD operations in segments of the DRAM row; and (ii) to the DRAM I/O circuitry to allow data to move across DRAM columns (enabling native support for PuD reduction operations). On the software side, MIMDRAM implements compiler passes to (i) identify and generate PuD operations with the appropriate single-instruction multiple-data (SIMD) granularity; and (ii) schedule the concurrent execution of independent PuD operations. We evaluate MIMDRAM using several real-world applications. Our evaluation shows that MIMDRAM achieves 18.6× the utilization, 14.3× the energy efficiency, 1.7× the throughput, and 1.3× the fairness of a state-of-the-art PuD framework; and 30.6×/6.8× the energy efficiency of a high-end CPU/GPU. MIMDRAM adds minimal area cost on top of a DRAM chip (1.11%) and CPU die (0.6%).

4. HPCA

   Functionally-Complete Boolean Logic in DRAM: An Experimental Characterization and Analysis of Real DRAM Chips

   Ismail Emir Yuksel, Yahya Can Tugrul, Ataberk Olgun, Nisa Bostanci, Giray Yaglikci, Geraldo F. Oliveira, Haocong Luo, Juan Gomez Luna, Mohammad Sadrosadati, and Onur Mutlu

   In HPCA, 2024
5. HPCA

   CoMeT: Count-Min Sketch-based Row Tracking to Mitigate RowHammer with Low Cost

   Nisa Bostanci, Ismail Emir Yuksel, Ataberk Olgun, Konstantinos Kanellopoulos, Yahya Can Tugrul, Giray Yaglikci, Mohammad Sadrosadati, and Onur Mutlu

   In HPCA, 2024
6. HPCA

   Spatial Variation-Aware Read Disturbance Defenses: Experimental Analysis of Real DRAM Chips and Implications on Future Solutions

   Giray Yaglikci, Geraldo F. Oliveira, Yahya Can Tugrul, Ismail Emir Yuksel, Ataberk Olgun, Haocong Luo, and Onur Mutlu

   In HPCA, 2024
7. DSN

   Read Disturbance in High Bandwidth Memory: A Detailed Experimental Study on HBM2 DRAM Chips

   Ataberk Olgun, Majd Osseiran, Yahya Can Tuğrul, Haocong Luo, Steve Rhyner, Behzad Salami, Juan Gomez Luna, and Onur Mutlu

   In DSN, 2024

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   We experimentally demonstrate the effects of read disturbance (RowHammer and RowPress) and uncover the inner workings of undocumented read disturbance defense mechanisms in High Bandwidth Memory (HBM). Detailed characterization of six real HBM2 DRAM chips in two different FPGA boards shows that (1) the read disturbance vulnerability significantly varies between different HBM2 chips and between different components (e.g., 3D-stacked channels) inside a chip, (2) DRAM rows at the end and in the middle of a bank are more resilient to read disturbance, (3) fewer additional activations are sufficient to induce more read disturbance bitflips in a DRAM row if the row exhibits the first bitflip at a relatively high activation count, (4) a modern HBM2 chip implements undocumented read disturbance defenses that track potential aggressor rows based on how many times they are activated. We describe how our findings could be leveraged to develop more powerful read disturbance attacks and more efficient defense mechanisms.

   @inproceedings{olgun2024experimental,
     title = {{Read Disturbance in High Bandwidth Memory: A Detailed Experimental Study on HBM2 DRAM Chips}},
     author = {Olgun, Ataberk and Osseiran, Majd and Tu{\u{g}}rul, Yahya Can and Luo, Haocong and Rhyner, Steve and Salami, Behzad and Luna, Juan Gomez and Mutlu, Onur},
     booktitle = {DSN},
     year = {2024},
   }

8. DSN

   Simultaneous Many-Row Activation in Off-the-Shelf DRAM Chips: Experimental Characterization and Analysis

   Ismail Emir Yuksel, Yahya Can Tugrul, F Bostanci, Geraldo F Oliveira, A Giray Yaglikci, Ataberk Olgun, Melina Soysal, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, and Onur Mutlu

   In DSN, 2024

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   We experimentally analyze the computational capability of commercial off-the-shelf (COTS) DRAM chips and the robustness of these capabilities under various timing delays between DRAM commands, data patterns, temperature, and voltage levels. We extensively characterize 120 COTS DDR4 chips from two major manufacturers. We highlight four key results of our study. First, COTS DRAM chips are capable of 1) simultaneously activating up to 32 rows (i.e., simultaneous many-row activation), 2) executing a majority of X (MAJX) operation where X>3 (i.e., MAJ5, MAJ7, and MAJ9 operations), and 3) copying a DRAM row (concurrently) to up to 31 other DRAM rows, which we call Multi-RowCopy. Second, storing multiple copies of MAJX’s input operands on all simultaneously activated rows drastically increases the success rate (i.e., the percentage of DRAM cells that correctly perform the computation) of the MAJX operation. For example, MAJ3 with 32-row activation (i.e., replicating each MAJ3’s input operands 10 times) has a 30.81% higher average success rate than MAJ3 with 4-row activation (i.e., no replication). Third, data pattern affects the success rate of MAJX and Multi-RowCopy operations by 11.52% and 0.07% on average. Fourth, simultaneous many-row activation, MAJX, and Multi-RowCopy operations are highly resilient to temperature and voltage changes, with small success rate variations of at most 2.13% among all tested operations. We believe these empirical results demonstrate the promising potential of using DRAM as a computation substrate.

   @inproceedings{yuksel2024simultaneous,
     title = {{Simultaneous Many-Row Activation in Off-the-Shelf DRAM Chips: Experimental Characterization and Analysis}},
     author = {Yuksel, Ismail Emir and Tugrul, Yahya Can and Bostanci, F and Oliveira, Geraldo F and Yaglikci, A Giray and Olgun, Ataberk and Soysal, Melina and Luo, Haocong and G{\'o}mez-Luna, Juan and Sadrosadati, Mohammad and Mutlu, Onur},
     booktitle = {DSN},
     year = {2024}
   }

9. IEEE Access

   SpyHammer: Understanding and Exploiting RowHammer under Fine-Grained Temperature Variations

   Lois Orosa, Ulrich Rührmair, A. Giray Yaglikci, Haocong Luo, Ataberk Olgun, Patrick Jattke, Minesh Patel, Jeremie Kim, Kaveh Razavi, and Onur Mutlu

   IEEE Access, 2024

   Bib PDF

   @article{orosa2024spyhammer,
     author = {Orosa, Lois and Rührmair, Ulrich and Giray Yaglikci, A. and Luo, Haocong and Olgun, Ataberk and Jattke, Patrick and Patel, Minesh and Kim, Jeremie and Razavi, Kaveh and Mutlu, Onur},
     journal = {IEEE Access},
     title = {{SpyHammer: Understanding and Exploiting RowHammer under Fine-Grained Temperature Variations}},
     year = {2024}
   }

10. MICRO

    Self-Managing DRAM: A Low-Cost Framework for Enabling Autonomous and Efficient in-DRAM Operations

    Hasan Hassan, Ataberk Olgun, A. Giray Yaglikci, Haocong Luo, and Onur Mutlu

    In MICRO, 2024

    Bib PDF Code

    @inproceedings{hassan2024self,
      title = {{Self-Managing DRAM: A Low-Cost Framework for Enabling Autonomous and Efficient in-DRAM Operations}},
      author = {Hassan, Hasan and Olgun, Ataberk and Yaglikci, A. Giray and Luo, Haocong and Mutlu, Onur},
      booktitle = {MICRO},
      year = {2024},
    }

2023

1. ASP-DAC

   Fundamentally Understanding and Solving RowHammer

   Onur Mutlu, Ataberk Olgun, and A Giray Yağlıkcı

   In ASP-DAC, 2023

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   We provide an overview of recent developments and future directions in the RowHammer vulnerability that plagues modern DRAM (Dynamic Random Memory Access) chips, which are used in almost all computing systems as main memory. RowHammer is the phenomenon in which repeatedly accessing a row in a real DRAM chip causes bitflips (i.e., data corruption) in physically nearby rows. This phenomenon leads to a serious and widespread system security vulnerability, as many works since the original RowHammer paper in 2014 have shown. Recent analysis of the RowHammer phenomenon reveals that the problem is getting much worse as DRAM technology scaling continues: newer DRAM chips are fundamentally more vulnerable to RowHammer at the device and circuit levels. Deeper analysis of RowHammer shows that there are many dimensions to the problem as the vulnerability is sensitive to many variables, including environmental conditions (temperature & voltage), process variation, stored data patterns, as well as memory access patterns and memory control policies. As such, it has proven difficult to devise fully-secure and very efficient (i.e., low-overhead in performance, energy, area) protection mechanisms against RowHammer and attempts made by DRAM manufacturers have been shown to lack security guarantees. After reviewing various recent developments in exploiting, understanding, and mitigating RowHammer, we discuss future directions that we believe are critical for solving the RowHammer problem. We argue for two major directions to amplify research and development efforts in: 1) building a much deeper understanding of the problem and its many dimensions, in both cutting-edge DRAM chips and computing systems deployed in the field, and 2) the design and development of extremely efficient and fully-secure solutions via system-memory cooperation.

   @inproceedings{mutlu2023fundamentally,
     title = {{Fundamentally Understanding and Solving RowHammer}},
     author = {Mutlu, Onur and Olgun, Ataberk and Ya{\u{g}}l{\i}kc{\i}, A Giray},
     booktitle = {ASP-DAC},
     year = {2023}
   }

2. ACM TACO

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

   Ataberk Olgun, Juan Gómez Luna, Konstantinos Kanellopoulos, Behzad Salami, Hasan Hassan, Oguz Ergin, and Onur Mutlu

   ACM TACO, 2023

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   Processing-using-memory (PuM) techniques leverage the analog operation of memory cells to perform computation. Several recent works have demonstrated PuM techniques in off-the-shelf DRAM devices. Since DRAM is the dominant memory technology as main memory in current computing systems, these PuM techniques represent an opportunity for alleviating the data movement bottleneck at very low cost. However, system integration of PuM techniques imposes non-trivial challenges that are yet to be solved. Design space exploration of potential solutions to the PuM integration challenges requires appropriate tools to develop necessary hardware and software components. Unfortunately, current specialized DRAM-testing platforms, or system simulators do not provide the flexibility and/or the holistic system view that is necessary to deal with PuM integration challenges. We design and develop PiDRAM, the first flexible end-to-end framework that enables system integration studies and evaluation of real PuM techniques. PiDRAM provides software and hardware components to rapidly integrate PuM techniques across the whole system software and hardware stack (e.g., necessary modifications in the operating system, memory controller). We implement PiDRAM on an FPGA-based platform along with an open-source RISC-V system. Using PiDRAM, we implement and evaluate two state-of-the-art PuM techniques: in-DRAM (i) copy and initialization, (ii) true random number generation. Our results show that the in-memory copy and initialization techniques can improve the performance of bulk copy operations by 12.6x and bulk initialization operations by 14.6x on a real system. Implementing the true random number generator requires only 190 lines of Verilog and 74 lines of C code using PiDRAM’s software and hardware components.

   @article{olgun2023pidram,
     title = {{PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAM}},
     author = {Olgun, Ataberk and Luna, Juan G{\'o}mez and Kanellopoulos, Konstantinos and Salami, Behzad and Hassan, Hasan and Ergin, Oguz and Mutlu, Onur},
     journal = {ACM TACO},
     year = {2023}
   }

3. DSN

   An Experimental Analysis of RowHammer in HBM2 DRAM Chips

   Ataberk Olgun, Majd Osseiran, Yahya Can Tuğrul, Haocong Luo, Steve Rhyner, Behzad Salami, Juan Gomez Luna, and Onur Mutlu

   In DSN Disrupt, 2023

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   RowHammer (RH) is a significant and worsening security, safety, and reliability issue of modern DRAM chips that can be exploited to break memory isolation. Therefore, it is important to understand real DRAM chips’ RH characteristics. Unfortunately, no prior work extensively studies the RH vulnerability of modern 3D-stacked high-bandwidth memory (HBM) chips, which are commonly used in modern GPUs. In this work, we experimentally characterize the RH vulnerability of a real HBM2 DRAM chip. We show that 1) different 3D-stacked channels of HBM2 memory exhibit significantly different levels of RH vulnerability (up to 79% difference in bit error rate), 2) the DRAM rows at the end of a DRAM bank (rows with the highest addresses) exhibit significantly fewer RH bitflips than other rows, and 3) a modern HBM2 DRAM chip implements undisclosed RH defenses that are triggered by periodic refresh operations. We describe the implications of our observations on future RH attacks and defenses and discuss future work for understanding RH in 3D-stacked memories.

   @inproceedings{olgun2023experimental,
     title = {{An Experimental Analysis of RowHammer in HBM2 DRAM Chips}},
     author = {Olgun, Ataberk and Osseiran, Majd and Tu{\u{g}}rul, Yahya Can and Luo, Haocong and Rhyner, Steve and Salami, Behzad and Luna, Juan Gomez and Mutlu, Onur},
     booktitle = {DSN Disrupt},
     year = {2023},
   }

4. IEEE TCAD

   DRAM Bender: An Extensible and Versatile FPGA-based Infrastructure to Easily Test State-of-the-art DRAM Chips

   Ataberk Olgun, Hasan Hassan, A Giray Yağlıkçı, Yahya Can Tuğrul, Lois Orosa, Haocong Luo, Minesh Patel, Oğuz Ergin, and Onur Mutlu

   IEEE TCAD, 2023

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   To understand and improve DRAM performance, reliability, security and energy efficiency, prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art open source infrastructures capable of conducting such studies are obsolete, poorly supported, or difficult to use, or their inflexibility limit the types of studies they can conduct. We propose DRAM Bender, a new FPGA-based infrastructure that enables experimental studies on state-of-the-art DRAM chips. DRAM Bender offers three key features at the same time. First, DRAM Bender enables directly interfacing with a DRAM chip through its low-level interface. This allows users to issue DRAM commands in arbitrary order and with finer-grained time intervals compared to other open source infrastructures. Second, DRAM Bender exposes easy-to-use C++ and Python programming interfaces, allowing users to quickly and easily develop different types of DRAM experiments. Third, DRAM Bender is easily extensible. The modular design of DRAM Bender allows extending it to (i) support existing and emerging DRAM interfaces, and (ii) run on new commercial or custom FPGA boards with little effort. To demonstrate that DRAM Bender is a versatile infrastructure, we conduct three case studies, two of which lead to new observations about the DRAM RowHammer vulnerability. In particular, we show that data patterns supported by DRAM Bender uncovers a larger set of bit-flips on a victim row compared to the data patterns commonly used by prior work. We demonstrate the extensibility of DRAM Bender by implementing it on five different FPGAs with DDR4 and DDR3 support.

   @article{olgun2023dram,
     title = {{DRAM Bender: An Extensible and Versatile FPGA-based Infrastructure to Easily Test State-of-the-art DRAM Chips}},
     author = {Olgun, Ataberk and Hassan, Hasan and Ya{\u{g}}l{\i}k{\c{c}}{\i}, A Giray and Tu{\u{g}}rul, Yahya Can and Orosa, Lois and Luo, Haocong and Patel, Minesh and Ergin, O{\u{g}}uz and Mutlu, Onur},
     journal = {IEEE TCAD},
     year = {2023}
   }

5. ISCA

   RowPress: Amplifying Read Disturbance in Modern DRAM Chips

   Haocong Luo, Ataberk Olgun, Abdullah Giray Yağlıkçı, Yahya Can Tuğrul, Steve Rhyner, Meryem Banu Cavlak, Joël Lindegger, Mohammad Sadrosadati, and Onur Mutlu

   In ISCA, 2023

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   Memory isolation is critical for system reliability, security, and safety. Unfortunately, read disturbance can break memory isolation in modern DRAM chips. For example, RowHammer is a well-studied read-disturb phenomenon where repeatedly opening and closing (i.e., hammering) a DRAM row many times causes bitflips in physically nearby rows. This paper experimentally demonstrates and analyzes another widespread read-disturb phenomenon, RowPress, in real DDR4 DRAM chips. RowPress breaks memory isolation by keeping a DRAM row open for a long period of time, which disturbs physically nearby rows enough to cause bitflips. We show that RowPress amplifies DRAM’s vulnerability to read-disturb attacks by significantly reducing the number of row activations needed to induce a bitflip by one to two orders of magnitude under realistic conditions. In extreme cases, RowPress induces bitflips in a DRAM row when an adjacent row is activated only once. Our detailed characterization of 164 real DDR4 DRAM chips shows that RowPress 1) affects chips from all three major DRAM manufacturers, 2) gets worse as DRAM technology scales down to smaller node sizes, and 3) affects a different set of DRAM cells from RowHammer and behaves differently from RowHammer as temperature and access pattern changes. We demonstrate in a real DDR4-based system with RowHammer protection that 1) a user-level program induces bitflips by leveraging RowPress while conventional RowHammer cannot do so, and 2) a memory controller that adaptively keeps the DRAM row open for a longer period of time based on access pattern can facilitate RowPress-based attacks. To prevent bitflips due to RowPress, we describe and evaluate a new methodology that adapts existing RowHammer mitigation techniques to also mitigate RowPress with low additional performance overhead. We open source all our code and data to facilitate future research on RowPress.

   @inproceedings{luo2023rowpress,
     title = {{RowPress: Amplifying Read Disturbance in Modern DRAM Chips}},
     author = {Luo, Haocong and Olgun, Ataberk and Ya{\u{g}}l{\i}k{\c{c}}{\i}, Abdullah Giray and Tu{\u{g}}rul, Yahya Can and Rhyner, Steve and Cavlak, Meryem Banu and Lindegger, Jo{\"e}l and Sadrosadati, Mohammad and Mutlu, Onur},
     booktitle = {ISCA},
     year = {2023}
   }

2022

1. HPCA

   DR-STRaNGe: End-to-End System Design for DRAM-Based True Random Number Generators

   F Nisa Bostancı, Ataberk Olgun, Lois Orosa, A Giray Yağlıkçı, Jeremie S Kim, Hasan Hassan, Oğuz Ergin, and Onur Mutlu

   In HPCA, 2022

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   Random number generation is an important task in a wide variety of critical applications including cryptographic algorithms, scientific simulations, and industrial testing tools. True Random Number Generators (TRNGs) produce truly random data by sampling a physical entropy source that typically requires custom hardware and suffers from long latency. To enable high-bandwidth and low-latency TRNGs on commodity devices, recent works propose TRNGs that use DRAM as an entropy source. Although prior works demonstrate promising DRAM-based TRNGs, integration of such mechanisms into real systems poses challenges. We identify three challenges for using DRAM-based TRNGs in current systems: (1) generating random numbers can degrade system performance by slowing down concurrently-running applications due to the interference between RNG and regular memory operations in the memory controller (i.e., RNG interference), (2) this RNG interference can degrade system fairness by unfairly prioritizing applications that intensively use random numbers (i.e., RNG applications), and (3) RNG applications can experience significant slowdowns due to the high RNG latency. We propose DR-STRaNGe, an end-to-end system design for DRAM-based TRNGs that (1) reduces the RNG interference by separating RNG requests from regular requests in the memory controller, (2) improves the system fairness with an RNG-aware memory request scheduler, and (3) hides the large TRNG latencies using a random number buffering mechanism with a new DRAM idleness predictor that accurately identifies idle DRAM periods. We evaluate DR-STRaNGe using a set of 186 multiprogrammed workloads. Compared to an RNG-oblivious baseline system, DR-STRaNGe improves the average performance of non-RNG and RNG applications by 17.9% and 25.1%, respectively. DR-STRaNGe improves average system fairness by 32.1% and reduces average energy consumption by 21%.

   @inproceedings{bostanci2022dr,
     title = {{DR-STRaNGe: End-to-End System Design for DRAM-Based True Random Number Generators}},
     author = {Bostanc{\i}, F Nisa and Olgun, Ataberk and Orosa, Lois and Ya{\u{g}}l{\i}k{\c{c}}{\i}, A Giray and Kim, Jeremie S and Hassan, Hasan and Ergin, O{\u{g}}uz and Mutlu, Onur},
     booktitle = {HPCA},
     year = {2022}
   }

2. ASPLOS

   GenStore: a High-Performance In-Storage Processing System for Genome Sequence Analysis

   Nika Mansouri Ghiasi, Jisung Park, Harun Mustafa, Jeremie Kim, Ataberk Olgun, Arvid Gollwitzer, Damla Senol Cali, Can Firtina, Haiyu Mao, Nour Almadhoun Alserr, and  others

   In ASPLOS, 2022

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   Read mapping is a fundamental, yet computationally-expensive step in many genomics applications. It is used to identify potential matches and differences between fragments (called reads) of a sequenced genome and an already known genome (called a reference genome). To address the computational challenges in genome analysis, many prior works propose various approaches such as filters that select the reads that must undergo expensive computation, efficient heuristics, and hardware acceleration. While effective at reducing the computation overhead, all such approaches still require the costly movement of a large amount of data from storage to the rest of the system, which can significantly lower the end-to-end performance of read mapping in conventional and emerging genomics systems. We propose GenStore, the first in-storage processing system designed for genome sequence analysis that greatly reduces both data movement and computational overheads of genome sequence analysis by exploiting low-cost and accurate in-storage filters. GenStore leverages hardware/software co-design to address the challenges of in-storage processing, supporting reads with 1) different read lengths and error rates, and 2) different degrees of genetic variation. Through rigorous analysis of read mapping processes, we meticulously design low-cost hardware accelerators and data/computation flows inside a NAND flash-based SSD. Our evaluation using a wide range of real genomic datasets shows that GenStore, when implemented in three modern SSDs, significantly improves the read mapping performance of state-of-the-art software (hardware) baselines by 2.07-6.05× (1.52-3.32X) for read sets with high similarity to the reference genome and 1.45-33.63X (2.70-19.2X) for read sets with low similarity to the reference genome.

   @inproceedings{mansouri2022genstore,
     title = {{GenStore: a High-Performance In-Storage Processing System for Genome Sequence Analysis}},
     author = {Mansouri Ghiasi, Nika and Park, Jisung and Mustafa, Harun and Kim, Jeremie and Olgun, Ataberk and Gollwitzer, Arvid and Senol Cali, Damla and Firtina, Can and Mao, Haiyu and Almadhoun Alserr, Nour and others},
     booktitle = {ASPLOS},
     year = {2022},
   }

3. ACM TACO

   MetaSys: A Practical Open-Source Metadata Management System to Implement and Evaluate Cross-Layer Optimizations

   Nandita Vijaykumar, Ataberk Olgun, Konstantinos Kanellopoulos, F Nisa Bostanci, Hasan Hassan, Mehrshad Lotfi, Phillip B Gibbons, and Onur Mutlu

   ACM TACO, 2022

   Abs Bib PDF Code

   This paper introduces the first open-source FPGA-based infrastructure, MetaSys, with a prototype in a RISC-V core, to enable the rapid implementation and evaluation of a wide range of cross-layer techniques in real hardware. Hardware-software cooperative techniques are powerful approaches to improve the performance, quality of service, and security of general-purpose processors. They are however typically challenging to rapidly implement and evaluate in real hardware as they require full-stack changes to the hardware, OS, system software, and instruction-set architecture (ISA). MetaSys implements a rich hardware-software interface and lightweight metadata support that can be used as a common basis to rapidly implement and evaluate new cross-layer techniques. We demonstrate MetaSys’s versatility and ease-of-use by implementing and evaluating three cross-layer techniques for: (i) prefetching for graph analytics; (ii) bounds checking in memory unsafe languages, and (iii) return address protection in stack frames; each technique only requiring  100 lines of Chisel code over MetaSys. Using MetaSys, we perform the first detailed experimental study to quantify the performance overheads of using a single metadata management system to enable multiple cross-layer optimizations in CPUs. We identify the key sources of bottlenecks and system inefficiency of a general metadata management system. We design MetaSys to minimize these inefficiencies and provide increased versatility compared to previously-proposed metadata systems. Using three use cases and a detailed characterization, we demonstrate that a common metadata management system can be used to efficiently support diverse cross-layer techniques in CPUs.

   @article{vijaykumar2022metasys,
     title = {{MetaSys: A Practical Open-Source Metadata Management System to Implement and Evaluate Cross-Layer Optimizations}},
     author = {Vijaykumar, Nandita and Olgun, Ataberk and Kanellopoulos, Konstantinos and Bostanci, F Nisa and Hassan, Hasan and Lotfi, Mehrshad and Gibbons, Phillip B and Mutlu, Onur},
     journal = {ACM TACO},
     year = {2022}
   }

4. DSN

   Understanding RowHammer Under Reduced Wordline Voltage: An Experimental Study Using Real DRAM Devices

   A Giray Yağlıkçı, Haocong Luo, Geraldo F De Oliviera, Ataberk Olgun, Minesh Patel, Jisung Park, Hasan Hassan, Jeremie S Kim, Lois Orosa, and Onur Mutlu

   In DSN, 2022

   Abs Bib PDF

   RowHammer is a circuit-level DRAM vulnerability, where repeatedly activating and precharging a DRAM row, and thus alternating the voltage of a row’s wordline between low and high voltage levels, can cause bit flips in physically nearby rows. Recent DRAM chips are more vulnerable to RowHammer: with technology node scaling, the minimum number of activate-precharge cycles to induce a RowHammer bit flip reduces and the RowHammer bit error rate increases. Therefore, it is critical to develop effective and scalable approaches to protect modern DRAM systems against RowHammer. To enable such solutions, it is essential to develop a deeper understanding of the RowHammer vulnerability of modern DRAM chips. However, even though the voltage toggling on a wordline is a key determinant of RowHammer vulnerability, no prior work experimentally demonstrates the effect of wordline voltage (VPP) on the RowHammer vulnerability. Our work closes this gap in understanding. This is the first work to experimentally demonstrate on 272 real DRAM chips that lowering VPP reduces a DRAM chip’s RowHammer vulnerability. We show that lowering VPP 1) increases the number of activate-precharge cycles needed to induce a RowHammer bit flip by up to 85.8% with an average of 7.4% across all tested chips and 2) decreases the RowHammer bit error rate by up to 66.9% with an average of 15.2% across all tested chips. At the same time, reducing VPP marginally worsens a DRAM cell’s access latency, charge restoration, and data retention time within the guardbands of system-level nominal timing parameters for 208 out of 272 tested chips. We conclude that reducing VPP is a promising strategy for reducing a DRAM chip’s RowHammer vulnerability without requiring modifications to DRAM chips.

   @inproceedings{yaglikci2022understanding,
     title = {{Understanding RowHammer Under Reduced Wordline Voltage: An Experimental Study Using Real DRAM Devices}},
     author = {Ya{\u{g}}l{\i}k{\c{c}}{\i}, A Giray and Luo, Haocong and De Oliviera, Geraldo F and Olgun, Ataberk and Patel, Minesh and Park, Jisung and Hassan, Hasan and Kim, Jeremie S and Orosa, Lois and Mutlu, Onur},
     booktitle = {DSN},
     year = {2022}
   }

5. DSN

   ERIC: An Efficient and Practical Software Obfuscation Framework

   Alperen Bolat, Seyyid Hikmet Celik, Ataberk Olgun, Oğuz Ergin, and Marco Ottavi

   In DSN, 2022

   Abs Bib PDF Code

   Modern cloud computing systems distribute software executables over a network to keep the software sources, which are typically compiled in a security-critical cluster, secret. We develop ERIC, a new, efficient, and general software obfuscation framework. ERIC protects software against (i) static analysis, by making only an encrypted version of software executables available to the human eye, no matter how the software is distributed, and (ii) dynamic analysis, by guaranteeing that an encrypted executable can only be correctly decrypted and executed by a single authenticated device. ERIC comprises key hardware and software components to provide efficient software obfuscation support: (i) a hardware decryption engine (HDE) enables efficient decryption of encrypted hardware in the target device, (ii) the compiler can seamlessly encrypt software executables given only a unique device identifier. Both the hardware and software components are ISA-independent, making ERIC general. The key idea of ERIC is to use physical unclonable functions (PUFs), unique device identifiers, as secret keys in encrypting software executables. Malicious parties that cannot access the PUF in the target device cannot perform static or dynamic analyses on the encrypted binary. We develop ERIC’s prototype on an FPGA to evaluate it end-to-end. Our prototype extends RISC-V Rocket Chip with the hardware decryption engine (HDE) to minimize the overheads of software decryption. We augment the custom LLVM-based compiler to enable partial/full encryption of RISC-V executables. The HDE incurs minor FPGA resource overheads, it requires 2.63% more LUTs and 3.83% more flip-flops compared to the Rocket Chip baseline. LLVM-based software encryption increases compile time by 15.22% and the executable size by 1.59%.

   @inproceedings{bolat2022eric,
     title = {{ERIC: An Efficient and Practical Software Obfuscation Framework}},
     author = {Bolat, Alperen and Celik, Seyyid Hikmet and Olgun, Ataberk and Ergin, O{\u{g}}uz and Ottavi, Marco},
     booktitle = {DSN},
     year = {2022}
   }

6. MICRO

   Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction

   Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadat, and Onur Mutlu

   In MICRO, 2022

   Abs Bib PDF Code

   Long-latency load requests continue to limit the performance of high-performance processors. To increase the latency tolerance of a processor, architects have primarily relied on two key techniques: sophisticated data prefetchers and large on-chip caches. In this work, we show that: 1) even a sophisticated state-of-the-art prefetcher can only predict half of the off-chip load requests on average across a wide range of workloads, and 2) due to the increasing size and complexity of on-chip caches, a large fraction of the latency of an off-chip load request is spent accessing the on-chip cache hierarchy. The goal of this work is to accelerate off-chip load requests by removing the on-chip cache access latency from their critical path. To this end, we propose a new technique called Hermes, whose key idea is to: 1) accurately predict which load requests might go off-chip, and 2) speculatively fetch the data required by the predicted off-chip loads directly from the main memory, while also concurrently accessing the cache hierarchy for such loads. To enable Hermes, we develop a new lightweight, perceptron-based off-chip load prediction technique that learns to identify off-chip load requests using multiple program features (e.g., sequence of program counters). For every load request, the predictor observes a set of program features to predict whether or not the load would go off-chip. If the load is predicted to go off-chip, Hermes issues a speculative request directly to the memory controller once the load’s physical address is generated. If the prediction is correct, the load eventually misses the cache hierarchy and waits for the ongoing speculative request to finish, thus hiding the on-chip cache hierarchy access latency from the critical path of the off-chip load. Our evaluation shows that Hermes significantly improves performance of a state-of-the-art baseline. We open-source Hermes.

   @inproceedings{bera2022hermes,
     title = {{Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction}},
     author = {Bera, Rahul and Kanellopoulos, Konstantinos and Balachandran, Shankar and Novo, David and Olgun, Ataberk and Sadrosadat, Mohammad and Mutlu, Onur},
     booktitle = {MICRO},
     year = {2022}
   }

7. MICRO

   HiRA: Hidden Row Activation for Reducing Refresh Latency of Off-the-Shelf DRAM Chips

   A Giray Yağlikçi, Ataberk Olgun, Minesh Patel, Haocong Luo, Hasan Hassan, Lois Orosa, Oğuz Ergin, and Onur Mutlu

   In MICRO, 2022

   Abs Bib PDF

   DRAM is the building block of modern main memory systems. DRAM cells must be periodically refreshed to prevent data loss. Refresh operations degrade system performance by interfering with memory accesses. As DRAM chip density increases with technology node scaling, refresh operations also increase because: 1) the number of DRAM rows in a chip increases; and 2) DRAM cells need additional refresh operations to mitigate bit failures caused by RowHammer, a failure mechanism that becomes worse with technology node scaling. Thus, it is critical to enable refresh operations at low performance overhead. To this end, we propose a new operation, Hidden Row Activation (HiRA), and the HiRA Memory Controller (HiRA-MC). HiRA hides a refresh operation’s latency by refreshing a row concurrently with accessing or refreshing another row within the same bank. Unlike prior works, HiRA achieves this parallelism without any modifications to off-the-shelf DRAM chips. To do so, it leverages the new observation that two rows in the same bank can be activated without data loss if the rows are connected to different charge restoration circuitry. We experimentally demonstrate on 56% real off-the-shelf DRAM chips that HiRA can reliably parallelize a DRAM row’s refresh operation with refresh or activation of any of the 32% of the rows within the same bank. By doing so, HiRA reduces the overall latency of two refresh operations by 51.4%. HiRA-MC modifies the memory request scheduler to perform HiRA when a refresh operation can be performed concurrently with a memory access or another refresh. Our system-level evaluations show that HiRA-MC increases system performance by 12.6% and 3.73x as it reduces the performance degradation due to periodic refreshes and refreshes for RowHammer protection (preventive refreshes), respectively, for future DRAM chips with increased density and RowHammer vulnerability

   @inproceedings{yaglikci2022hira,
     title = {HiRA: Hidden Row Activation for Reducing Refresh Latency of Off-the-Shelf DRAM Chips},
     author = {Ya{\u{g}}lik{\c{c}}i, A Giray and Olgun, Ataberk and Patel, Minesh and Luo, Haocong and Hassan, Hasan and Orosa, Lois and Ergin, O{\u{g}}uz and Mutlu, Onur},
     booktitle = {MICRO},
     year = {2022}
   }

2021

1. Masters Thesis

   Gerçek DRAM Aygıtlarında Dörtlü Etkinleştirme ile Yüksek Hızda Gerçek Rastgele Sayı Üretilmesi

   Ataberk Olgun

   TOBB ETÜ, 2021

   Bib PDF Code

   @mastersthesis{olgun2021gerccek,
     title = {{Ger{\c{c}}ek DRAM Ayg{\i}tlar{\i}nda D{\"o}rtl{\"u} Etkinle{\c{s}}tirme ile Y{\"u}ksek H{\i}zda Ger{\c{c}}ek Rastgele Say{\i} {\"U}retilmesi}},
     author = {Olgun, Ataberk},
     year = {2021},
     school = {TOBB ET{\"U}},
     dimensions = {true}
   }

2. HPCA

   Blockhammer: Preventing RowHammer at Low Cost by Blacklisting Rapidly-Accessed DRAM Rows

   A Giray Yağlikçi, Minesh Patel, Jeremie S Kim, Roknoddin Azizi, Ataberk Olgun, Lois Orosa, Hasan Hassan, Jisung Park, Konstantinos Kanellopoulos, Taha Shahroodi, and  others

   In HPCA, 2021

   Abs Bib PDF Code

   Aggressive memory density scaling causes modern DRAM devices to suffer from RowHammer, a phenomenon where rapidly activating a DRAM row can cause bit-flips in physically-nearby rows. Recent studies demonstrate that modern DRAM chips, including chips previously marketed as RowHammer-safe, are even more vulnerable to RowHammer than older chips. Many works show that attackers can exploit RowHammer bit-flips to reliably mount system-level attacks to escalate privilege and leak private data. Therefore, it is critical to ensure RowHammer-safe operation on all DRAM-based systems. Unfortunately, state-of-the-art RowHammer mitigation mechanisms face two major challenges. First, they incur increasingly higher performance and/or area overheads when applied to more vulnerable DRAM chips. Second, they require either proprietary information about or modifications to the DRAM chip design. In this paper, we show that it is possible to efficiently and scalably prevent RowHammer bit-flips without knowledge of or modification to DRAM internals. We introduce BlockHammer, a low-cost, effective, and easy-to-adopt RowHammer mitigation mechanism that overcomes the two key challenges by selectively throttling memory accesses that could otherwise cause RowHammer bit-flips. The key idea of BlockHammer is to (1) track row activation rates using area-efficient Bloom filters and (2) use the tracking data to ensure that no row is ever activated rapidly enough to induce RowHammer bit-flips. By doing so, BlockHammer (1) makes it impossible for a RowHammer bit-flip to occur and (2) greatly reduces a RowHammer attack’s impact on the performance of co-running benign applications. Compared to state-of-the-art RowHammer mitigation mechanisms, BlockHammer provides competitive performance and energy when the system is not under a RowHammer attack and significantly better performance and energy when the system is under attack.

   @inproceedings{yaglikci2021blockhammer,
     title = {{Blockhammer: Preventing RowHammer at Low Cost by Blacklisting Rapidly-Accessed DRAM Rows}},
     author = {Ya{\u{g}}lik{\c{c}}i, A Giray and Patel, Minesh and Kim, Jeremie S and Azizi, Roknoddin and Olgun, Ataberk and Orosa, Lois and Hassan, Hasan and Park, Jisung and Kanellopoulos, Konstantinos and Shahroodi, Taha and others},
     booktitle = {HPCA},
     year = {2021},
     dimensions = {true}
   }

3. ISCA

   QUAC-TRNG: High-Throughput True Random Number Generation Using Quadruple Row Activation in Commodity DRAM Chips

   Ataberk Olgun, Minesh Patel, A Giray Yağlıkçı, Haocong Luo, Jeremie S Kim, F Nisa Bostancı, Nandita Vijaykumar, Oğuz Ergin, and Onur Mutlu

   In ISCA, 2021

   Abs Bib PDF Code

   True random number generators (TRNG) sample random physical processes to create large amounts of random numbers for various use cases, including security-critical cryptographic primitives, scientific simulations, machine learning applications, and even recreational entertainment. Unfortunately, not every computing system is equipped with dedicated TRNG hardware, limiting the application space and security guarantees for such systems. To open the application space and enable security guarantees for the overwhelming majority of computing systems that do not necessarily have dedicated TRNG hardware, we develop QUAC-TRNG. QUAC-TRNG exploits the new observation that a carefully-engineered sequence of DRAM commands activates four consecutive DRAM rows in rapid succession. This QUadruple ACtivation (QUAC) causes the bitline sense amplifiers to non-deterministically converge to random values when we activate four rows that store conflicting data because the net deviation in bitline voltage fails to meet reliable sensing margins. We experimentally demonstrate that QUAC reliably generates random values across 136 commodity DDR4 DRAM chips from one major DRAM manufacturer. We describe how to develop an effective TRNG (QUAC-TRNG) based on QUAC. We evaluate the quality of our TRNG using NIST STS and find that QUAC-TRNG successfully passes each test. Our experimental evaluations show that QUAC-TRNG generates true random numbers with a throughput of 3.44 Gb/s (per DRAM channel), outperforming the state-of-the-art DRAM-based TRNG by 15.08x and 1.41x for basic and throughput-optimized versions, respectively. We show that QUAC-TRNG utilizes DRAM bandwidth better than the state-of-the-art, achieving up to 2.03x the throughput of a throughput-optimized baseline when scaling bus frequencies to 12 GT/s.

   @inproceedings{olgun2021quac,
     title = {{QUAC-TRNG: High-Throughput True Random Number Generation Using Quadruple Row Activation in Commodity DRAM Chips}},
     author = {Olgun, Ataberk and Patel, Minesh and Ya{\u{g}}l{\i}k{\c{c}}{\i}, A Giray and Luo, Haocong and Kim, Jeremie S and Bostanc{\i}, F Nisa and Vijaykumar, Nandita and Ergin, O{\u{g}}uz and Mutlu, Onur},
     booktitle = {ISCA},
     year = {2021},
     dimensions = {true}
   }

4. MICRO

   A Deeper Look into Rowhammer’s Sensitivities: Experimental Analysis of Real DRAM Chips and Implications on Future Attacks and Defenses

   Lois Orosa, Abdullah Giray Yaglikci, Haocong Luo, Ataberk Olgun, Jisung Park, Hasan Hassan, Minesh Patel, Jeremie S Kim, and Onur Mutlu

   In MICRO, 2021

   Abs Bib PDF

   RowHammer is a circuit-level DRAM vulnerability where repeatedly accessing (i.e., hammering) a DRAM row can cause bit flips in physically nearby rows. The RowHammer vulnerability worsens as DRAM cell size and cell-to-cell spacing shrink. Recent studies demonstrate that modern DRAM chips, including chips previously marketed as RowHammer-safe, are even more vulnerable to RowHammer than older chips such that the required hammer count to cause a bit flip has reduced by more than 10X in the last decade. Therefore, it is essential to develop a better understanding and in-depth insights into the RowHammer vulnerability of modern DRAM chips to more effectively secure current and future systems. Our goal in this paper is to provide insights into fundamental properties of the RowHammer vulnerability that are not yet rigorously studied by prior works, but can potentially be i) exploited to develop more effective RowHammer attacks or ii) leveraged to design more effective and efficient defense mechanisms. To this end, we present an experimental characterization using 248 DDR4 and 24 DDR3 modern DRAM chips from four major DRAM manufacturers demonstrating how the RowHammer effects vary with three fundamental properties: 1) DRAM chip temperature, 2) aggressor row active time, and 3) victim DRAM cell’s physical location. Among our 16 new observations, we highlight that a RowHammer bit flip 1) is very likely to occur in a bounded range, specific to each DRAM cell (e.g., 5.4% of the vulnerable DRAM cells exhibit errors in the range 70C to 90C), 2) is more likely to occur if the aggressor row is active for longer time (e.g., RowHammer vulnerability increases by 36% if we keep a DRAM row active for 15 column accesses), and 3) is more likely to occur in certain physical regions of the DRAM module under attack (e.g., 5% of the rows are 2x more vulnerable than the remaining 95% of the rows).

   @inproceedings{orosa2021deeper,
     title = {{A Deeper Look into Rowhammer’s Sensitivities: Experimental Analysis of Real DRAM Chips and Implications on Future Attacks and Defenses}},
     author = {Orosa, Lois and Yaglikci, Abdullah Giray and Luo, Haocong and Olgun, Ataberk and Park, Jisung and Hassan, Hasan and Patel, Minesh and Kim, Jeremie S and Mutlu, Onur},
     booktitle = {MICRO},
     year = {2021},
     dimensions = {true}
   }