ISCACitations/all_top75pct.csv at main · VerticalResearchGroup/ISCACitations · GitHub

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,citations,% of total,Cummulative,Title,
116,6825.0,9.317049996723673,0.09317049996723674,"(2017):In-Datacenter Performance Analysis of a Tensor Processing Unit"
58,3622.0,4.944520892034161,0.14261570888757835,"(2016):EIE: efficient inference engine on compressed deep neural network"
59,2558.0,3.4920166874167267,0.17753587576174562,"(2016):ISAAC: a convolutional neural network accelerator with in-situ analog arithmetic in crossbars"
60,2233.0,3.0483476399536946,0.20801935216128256,"(2016):Eyeriss: a spatial architecture for energy-efficient dataflow for convolutional neural networks"
61,2069.0,2.8244654129261955,0.2362640062905445,"(2016):PRIME: a novel processing-in-memory architecture for neural network computation in ReRAM-based main memory"
117,1705.0,2.327556079767599,0.2595395670882205,"(2017):SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks"
0,1467.0,2.002653823471594,0.27956610532293646,"(2015):ShiDianNao: shifting vision processing closer to the sensor"
1,1176.0,1.6053993840508485,0.29562009916344495,"(2015):A scalable processing-in-memory accelerator for parallel graph processing"
62,1001.0,1.366500666186139,0.30928510582530633,"(2016):Cnvlutin: ineffectual-neuron-free deep neural network computing"
63,825.0,1.1262368127907738,0.3205474739532141,"(2016):Minerva: enabling low-power, highly-accurate deep neural network accelerators"
170,760.0,1.0375030032981674,0.33092250398619577,"(2018):Bit fusion: bit-level dynamically composable architecture for accelerating deep neural networks"
171,758.0,1.0347727322368565,0.3412702313085643,"(2018):A configurable cloud-scale DNN processor for real-time AI"
2,747.0,1.0197562413996462,0.35146779372256076,"(2015):Heracles: improving resource efficiency at scale"
294,716.0,0.9774370399493261,0.361242164122054,"(2020):MLPerf inference benchmark"
3,709.0,0.9678810912347378,0.3709209750344014,"(2015):Profiling a warehouse-scale computer"
4,706.0,0.9637856846427713,0.3805588318808291,"(2015):PIM-enabled instructions: a low-overhead, locality-aware processing-in-memory architecture"
517,658.0,0.898259179171308,0.3895414236725422,"(2023):TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings"
64,589.0,0.8040648275560798,0.39758207194810297,"(2016):Neurocube: a programmable digital neuromorphic architecture with high-density 3D memory"
376,549.0,0.7494594063298604,0.4050766660114016,"(2021):Ten lessons from three generations shaped Google's TPUv4i"
172,545.0,0.7439988642072385,0.412516654653474,"(2018):Neural cache: bit-serial in-cache acceleration of deep neural networks"
118,523.0,0.7139658825328178,0.41965631347880217,"(2017):Scalpel: Customizing DNN Pruning to the Underlying Hardware Parallelism"
65,488.0,0.6661861389598759,0.4263181748684009,"(2016):Cambricon: an instruction set architecture for neural networks"
601,457.0,0.6238669375095559,0.43255684424349644,"(2024):Splitwise: Efficient Generative LLM Inference Using Phase Splitting"
119,443.0,0.6047550400803792,0.43860439464430023,"(2017):Maximizing CNN Accelerator Efficiency Through Resource Partitioning"
295,439.0,0.5992944979577572,0.4445973396238778,"(2020):Accel-sim: an extensible simulation framework for validated GPU modeling"
120,415.0,0.5665312452220257,0.45026265207609806,"(2017):Plasticine: A Reconfigurable Architecture For Parallel Paterns"
173,399.0,0.5446890767315379,0.4557095428434134,"(2018):Firesim: FPGA-accelerated cycle-exact scale-out system simulation in the public cloud"
66,377.0,0.5146560950571173,0.4608561037939846,"(2016):Biscuit: a framework for near-data processing of big data workloads"
67,359.0,0.4900836555053185,0.4657569403490378,"(2016):Transparent offloading and mapping (TOM): enabling programmer-transparent near-data processing in GPU systems"
377,358.0,0.48871851997466303,0.47064412554878443,"(2021):Hardware architecture and software stack for PIM based on commercial DRAM technology"
296,327.0,0.4463993185243431,0.47510811873402786,"(2020):RecNMP: accelerating personalized recommendation with near-memory processing"
174,309.0,0.4218268789725444,0.4793263875237533,"(2018):UCNN: exploiting computational reuse in deep neural networks via weight repetition"
121,302.0,0.41227093025795597,0.48344909682633286,"(2017):MCM-GPU: Multi-Chip-Module GPUs for Continued Performance Scalability"
122,301.0,0.4109057947273005,0.48755815477360587,"(2017):ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks"
68,285.0,0.3890636262368128,0.491448791035974,"(2016):RedEye: analog ConvNet image sensor architecture for continuous mobile vision"
69,284.0,0.3876984907061573,0.49532577594303556,"(2016):Back to the future: leveraging Belady's algorithm for improved cache replacement"
5,282.0,0.3849682196448463,0.49917545813948405,"(2015):Data reorganization in memory using 3D-stacked DRAM"
6,273.0,0.37268199986894696,0.5029022781381736,"(2015):BlueDBM: an appliance for big data analytics"
378,273.0,0.37268199986894696,0.5066290981368631,"(2021):Pioneering chiplet technology and design for the AMD EPYC™and Ryzen™processor families"
123,267.0,0.36449118668501407,0.5102740100037132,"(2017):Stream-Dataflow Acceleration"
7,266.0,0.3631260511543586,0.5139052705152568,"(2015):Redundant memory mappings for fast access to large memories"
457,264.0,0.3603957800930476,0.5175092283161873,"(2022):CraterLake: a hardware accelerator for efficient unbounded computation on encrypted data"
297,262.0,0.35766550903173666,0.5210858834065046,"(2020):Revisiting RowHammer: an experimental analysis of modern DRAM devices and mitigation techniques"
458,262.0,0.35766550903173666,0.524662538496822,"(2022):ACT: designing sustainable computer systems with an architectural carbon modeling tool"
234,253.0,0.3453792892558373,0.5281163313893804,"(2019):Sparse ReRAM engine: joint exploration of activation and weight sparsity in compressed neural networks"
175,250.0,0.34128388266387083,0.5315291702160191,"(2018):Energy-efficient neural network accelerator based on outlier-aware low-precision computation"
298,249.0,0.33991874713321535,0.5349283576873513,"(2020):DeepRecSys: a system for optimizing end-to-end at-scale neural recommendation inference"
176,232.0,0.31671144311207217,0.538095472118472,"(2018):SnaPEA: predictive early activation for reducing computation in deep convolutional neural networks"
235,230.0,0.3139811720507612,0.5412352838389796,"(2019):Full-stack, real-system quantum computer studies: architectural comparisons and design insights"
459,230.0,0.3139811720507612,0.5443750955594872,"(2022):BTS: an accelerator for bootstrappable fully homomorphic encryption"
379,228.0,0.31125090098945024,0.5474876045693816,"(2021):ELSA: hardware-software co-design for efficient, lightweight self-attention mechanism in neural networks"
70,227.0,0.3098857654587947,0.5505864622239696,"(2016):Energy efficient architecture for graph analytics accelerators"
236,215.0,0.29350413909092893,0.5535215036148788,"(2019):New attacks and defense for encrypted-address cache"
8,213.0,0.29077386802961797,0.556429242295175,"(2015):DjiNN and Tonic: DNN as a service and its implications for future warehouse scale computers"
124,211.0,0.288043596968307,0.559309678264858,"(2017):EDDIE: EM-Based Detection of Deviations in Program Execution"
125,210.0,0.2866784614376515,0.5621764628792345,"(2017):Regaining Lost Cycles with HotCalls: A Fast Interface for SGX Secure Enclaves"
71,200.0,0.2730271061310967,0.5649067339405455,"(2016):Dynamo: facebook's data center-wide power management system"
126,198.0,0.2702968350697857,0.5676097022912433,"(2017):Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient Descent"
9,197.0,0.26893169953913026,0.5702990192866346,"(2015):Rumba: an online quality management system for approximate computing"
237,196.0,0.2675665640084748,0.5729746849267193,"(2019):Asymptotic improvements to quantum circuits via qutrits"
238,195.0,0.26620142847781925,0.5756366992114975,"(2019):Statistical assertions for validating patterns and finding bugs in quantum programs"
177,193.0,0.26347115741650834,0.5782714107856626,"(2018):Gist: efficient data encoding for deep neural network training"
127,192.0,0.2621060218858528,0.5808924710045211,"(2017):Clank: Architectural Support for Intermittent Computation"
239,189.0,0.25801061529388636,0.58347257715746,"(2019):Accelerating distributed reinforcement learning with in-switch computing"
299,188.0,0.2566454797632309,0.5860390319550923,"(2020):DSAGEN: synthesizing programmable spatial accelerators"
380,185.0,0.25255007317126443,0.588564532686805,"(2021):CoSA: scheduling by constrained optimization for spatial accelerators"
240,179.0,0.24435925998733152,0.5910081252866783,"(2019):TWiCe: preventing row-hammering by exploiting time window counters"
128,178.0,0.24299412445667606,0.5934380665312451,"(2017):HeteroOS: OS Design for Heterogeneous Memory Management in Datacenter"
518,177.0,0.24162898892602058,0.5958543564205053,"(2023):OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization"
129,176.0,0.24026385339536507,0.5982569949544589,"(2017):The Reach Profiler (REAPER): Enabling the Mitigation of DRAM Retention Failures via Profiling at Aggressive Conditions"
241,172.0,0.23480331127274315,0.6006050280671864,"(2019):Duality cache for data parallel acceleration"
130,169.0,0.2307079046807767,0.6029121071139941,"(2017):Secure Hierarchy-Aware Cache Replacement Policy (SHARP): Defending Against Cache-Based Side Channel Atacks"
72,169.0,0.2307079046807767,0.6052191861608018,"(2016):ASIC clouds: specializing the datacenter"
10,168.0,0.2293427691501212,0.607512613852303,"(2015):Architecting to achieve a billion requests per second throughput on a single key-value store server platform"
73,166.0,0.22661249808881026,0.6097787388331911,"(2016):Automatic generation of efficient accelerators for reconfigurable hardware"
178,166.0,0.22661249808881026,0.6120448638140792,"(2018):Modular routing design for chiplet-based systems"
242,164.0,0.22388222702749927,0.6142836860843541,"(2019):CoNDA: efficient cache coherence support for near-data accelerators"
243,162.0,0.2211519559661883,0.616495205644016,"(2019):Efficient invisible speculative execution through selective delay and value prediction"
131,162.0,0.2211519559661883,0.618706725203678,"(2017):The Mondrian Data Engine"
244,159.0,0.21705654937422186,0.6208772906974201,"(2019):SoftSKU: optimizing server architectures for microservice diversity @scale"
245,158.0,0.21569141384356638,0.6230342048358558,"(2019):MGPUSim: enabling multi-GPU performance modeling and optimization"
300,158.0,0.21569141384356638,0.6251911189742915,"(2020):Centaur: a chiplet-based, hybrid sparse-dense accelerator for personalized recommendations"
11,156.0,0.21296114278225542,0.627320730402114,"(2015):Warped-compression: enabling power efficient GPUs through register compression"
74,155.0,0.21159600725159994,0.62943669047463,"(2016):Warped-slicer: efficient intra-SM slicing through dynamic resource partitioning for GPU multiprogramming"
246,154.0,0.21023087172094443,0.6315389991918394,"(2019):Laconic deep learning inference acceleration"
12,148.0,0.20204005853701157,0.6335593997772095,"(2015):Semantic locality and context-based prefetching using reinforcement learning"
301,147.0,0.20067492300635606,0.6355661490072732,"(2020):Think fast: a tensor streaming processor (TSP) for accelerating deep learning workloads"
302,143.0,0.19521438088373413,0.6375182928161105,"(2020):Xuantie-910: a commercial multi-core 12-stage pipeline out-of-order 64-bit high performance RISC-V processor with vector extension"
13,143.0,0.19521438088373413,0.6394704366249478,"(2015):A case for core-assisted bottleneck acceleration in GPUs: enabling flexible data compression with assist warps"
75,142.0,0.19384924535307865,0.6414089290784787,"(2016):Accelerating dependent cache misses with an enhanced memory controller"
179,142.0,0.19384924535307865,0.6433474215320095,"(2018):GraFboost: using accelerated flash storage for external graph analytics"
14,142.0,0.19384924535307865,0.6452859139855404,"(2015):A fully associative, tagless DRAM cache"
247,141.0,0.19248410982242314,0.6472107550837646,"(2019):Perceptron-based prefetch filtering"
303,140.0,0.1911189742917677,0.6491219448266823,"(2020):A multi-neural network acceleration architecture"
15,140.0,0.1911189742917677,0.6510331345696,"(2015):Flexible software profiling of GPU architectures"
16,139.0,0.1897538387611122,0.6529306729572111,"(2015):Flexible auto-refresh: enabling scalable and energy-efficient DRAM refresh reductions"
17,138.0,0.1883887032304567,0.6548145599895157,"(2015):Quantitative comparison of hardware transactional memory for Blue Gene/Q, zEnterprise EC12, Intel Core, and POWER8"
76,138.0,0.1883887032304567,0.6566984470218202,"(2016):Bit-plane compression: transforming data for better compression in many-core architectures"
304,137.0,0.18702356769980125,0.6585686826988183,"(2020):SpinalFlow: an architecture and dataflow tailored for spiking neural networks"
381,137.0,0.18702356769980125,0.6604389183758164,"(2021):Sparsity-aware and re-configurable NPU architecture for samsung flagship mobile SoC"
132,136.0,0.18565843216914574,0.6622955026975078,"(2017):Language-level persistency"
460,133.0,0.1815630255771793,0.6641111329532796,"(2022):PACMAN: attacking ARM pointer authentication with speculative execution"
180,131.0,0.17883275451586833,0.6658994604984383,"(2018):Genax: a genome sequencing accelerator"
18,131.0,0.17883275451586833,0.667687788043597,"(2015):CAWA: coordinated warp scheduling and cache prioritization for critical warp acceleration of GPGPU workloads"
181,130.0,0.17746761898521285,0.6694624642334491,"(2018):Enabling scientific computing on memristive accelerators"
248,127.0,0.1733722123932464,0.6711961863573815,"(2019):AsmDB: understanding and mitigating front-end stalls in warehouse-scale computers"
305,126.0,0.17200707686259092,0.6729162571260074,"(2020):MuonTrap: preventing cross-domain spectre-like attacks by capturing speculative state"
306,126.0,0.17200707686259092,0.6746363278946333,"(2020):DRQ: dynamic region-based quantization for deep neural network acceleration"
77,126.0,0.17200707686259092,0.6763563986632593,"(2016):Treadmill: attributing the source of tail latency through precise load testing and statistical inference"
182,125.0,0.17064194133193542,0.6780628180765786,"(2018):Euphrates: algorithm-SoC co-design for low-power mobile continuous vision"
184,125.0,0.17064194133193542,0.679769237489898,"(2018):GANAX: a unified MIMD-SIMD acceleration for generative adversarial networks"
183,125.0,0.17064194133193542,0.6814756569032174,"(2018):Mitigating wordline crosstalk using adaptive trees of counters"
185,123.0,0.16791167027062445,0.6831547736059237,"(2018):FLIN: enabling fairness and enhancing performance in modern NVMe solid state drives"
382,123.0,0.16791167027062445,0.68483389030863,"(2021):Dual-side sparse tensor core"
249,120.0,0.163816263678658,0.6864720529454166,"(2019):CROW: a low-cost substrate for improving DRAM performance, energy efficiency, and reliability"
383,120.0,0.163816263678658,0.6881102155822032,"(2021):RaPiD: AI accelerator for ultra-low precision training and inference"
250,120.0,0.163816263678658,0.6897483782189898,"(2019):MicroScope: enabling microarchitectural replay attacks"
186,119.0,0.16245112814800253,0.6913728895004698,"(2018):Computation reuse in DNNs by exploiting input similarity"
133,119.0,0.16245112814800253,0.6929974007819498,"(2017):Hybrid TLB Coalescing: Improving TLB Translation Coverage under Diverse Fragmented Memory Allocations"
187,119.0,0.16245112814800253,0.6946219120634298,"(2018):EVA2: exploiting temporal redundancy in live computer vision"
519,116.0,0.15835572155603608,0.6962054692789902,"(2023):FACT: FFN-Attention Co-optimized Transformer Architecture with Eager Correlation Prediction"
307,115.0,0.1569905860253806,0.697775375139244,"(2020):Bouquet of instruction pointers: instruction pointer classifier-based spatial hardware prefetching"
384,115.0,0.1569905860253806,0.6993452809994979,"(2021):Snafu: an ultra-low-power, energy-minimal CGRA-generation framework and architecture"
134,114.0,0.15562545049472512,0.7009015355044451,"(2017):ObfusMem: A Low-Overhead Access Obfuscation for Trusted Memories"
309,114.0,0.15562545049472512,0.7024577900093923,"(2020):iPIM: programmable in-memory image processing accelerator using near-bank architecture"
308,114.0,0.15562545049472512,0.7040140445143396,"(2020):Architecting noisy intermediate-scale trapped ion quantum computers"
251,112.0,0.15289517943341413,0.7055429963086737,"(2019):Interplay between hardware prefetcher and page eviction policy in CPU-GPU unified virtual memory"
19,110.0,0.15016490837210317,0.7070446453923948,"(2015):BEAR: techniques for mitigating bandwidth bloat in gigascale DRAM caches"
385,110.0,0.15016490837210317,0.7085462944761158,"(2021):PipeZK: accelerating zero-knowledge proof with a pipelined architecture"
20,109.0,0.1487997728414477,0.7100342922045303,"(2015):Hi-fi playback: tolerating position errors in shift operations of racetrack memory"
78,108.0,0.1474346373107922,0.7115086385776382,"(2016):XED: exposing on-die error detection information for strong memory reliability"
135,108.0,0.1474346373107922,0.7129829849507462,"(2017):Rethinking TLB Designs in Virtualized Environments: A Very Large Part-of-Memory TLB"
79,108.0,0.1474346373107922,0.7144573313238541,"(2016):Mellow writes: extending lifetime in resistive memories through selective slow write backs"
21,107.0,0.14606950178013672,0.7159180263416555,"(2015):Stash: have your scratchpad and cache it too"
310,106.0,0.14470436624948124,0.7173650700041503,"(2020):TIMELY: pushing data movements and interfaces in PIM accelerators towards local and in time domain"
520,104.0,0.14197409518817028,0.718784810956032,"(2023):RowPress: Amplifying Read Disturbance in Modern DRAM Chips"
386,104.0,0.14197409518817028,0.7202045519079137,"(2021):I see dead μops: leaking secrets via Intel/AMD micro-op caches"
136,104.0,0.14197409518817028,0.7216242928597953,"(2017):InvisiMem: Smart Memory Defenses for Memory Bus Side Channel"
252,103.0,0.1406089596575148,0.7230303824563705,"(2019):GraphSSD: graph semantics aware SSD"
137,103.0,0.1406089596575148,0.7244364720529457,"(2017):APPROX-NoC: A Data Approximation Framework for Network-On-Chip Architectures"
521,102.0,0.13924382412685932,0.7258289102942143,"(2023):SHARP: A Short-Word Hierarchical Accelerator for Robust and Practical Fully Homomorphic Encryption"
311,101.0,0.13787868859620384,0.7272076971801763,"(2020):Evolution of the samsung exynos CPU microarchitecture"
387,101.0,0.13787868859620384,0.7285864840661384,"(2021):FORMS: fine-grained polarized ReRAM-based in-situ computation for mixed-signal DNN accelerator"
522,101.0,0.13787868859620384,0.7299652709521004,"(2023):Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction"
461,100.0,0.13651355306554835,0.7313304064827559,"(2022):Hydra: enabling low-overhead mitigation of row-hammer at ultra-low thresholds via hybrid tracking"
188,100.0,0.13651355306554835,0.7326955420134115,"(2018):Prediction based execution on deep neural networks"
80,100.0,0.13651355306554835,0.734060677544067,"(2016):Agile paging: exceeding the best of nested and shadow paging"
138,100.0,0.13651355306554835,0.7354258130747225,"(2017):Access Pattern-Aware Cache Management for Improving Data Utilization in GPU"
388,99.0,0.13514841753489285,0.7367772972500715,"(2021):GoSPA: an energy-efficient high-performance globally optimized sparse convolutional neural network accelerator"
253,99.0,0.13514841753489285,0.7381287814254204,"(2019):Triad-NVM: persistency for integrity-protected and encrypted non-volatile memories"
255,97.0,0.13241814647358188,0.7394529628901562,"(2019):TIE: energy-efficient tensor train-based inference engine for deep neural network"
389,97.0,0.13241814647358188,0.740777144354892,"(2021):TENET: a framework for modeling tensor dataflow based on relation-centric notation"
254,97.0,0.13241814647358188,0.7421013258196277,"(2019):MnnFast: a fast and scalable system architecture for memory-augmented neural networks"
81,95.0,0.12968787541227092,0.7433982045737504,"(2016):Morpheus: creating application objects efficiently for heterogeneous computing"
390,95.0,0.12968787541227092,0.744695083327873,"(2021):HASCO: towards agile hardware and software co-design for tensor computation"
22,94.0,0.12832273988161544,0.7459783107266892,"(2015):Exploring the potential of heterogeneous von neumann/dataflow execution models"
23,94.0,0.12832273988161544,0.7472615381255053,"(2015):Unified address translation for memory-mapped SSDs with FlashMap"
256,94.0,0.12832273988161544,0.7485447655243215,"(2019):Anubis: ultra-low overhead and recovery time for secure non-volatile memories"
257,93.0,0.12695760435095996,0.7498143415678311,"(2019):Eager pruning: algorithm and architecture support for fast training of deep neural networks"
189,92.0,0.12559246882030448,0.7510702662560341,"(2018):RANA: towards efficient neural acceleration with refresh-optimized embedded DRAM"