BibSLEIGH — Babak

Travelled to:

1 × Austria
1 × France
1 × Mexico
1 × Spain
1 × United Kingdom
12 × USA

Collaborated with:

D.A.Wood A.Moshovos S.Yang T.N.Vijaykumar M.Ferdman A.Daglis Mark Sutherland M.D.Powell B.Grot E.Vlachos Y.O.Koçberber A.Ailamaki M.Coppola J.Goodacre G.Kornaros P.Lotfi-Kamran K.Balet I.Burcea S.Somogyi C.F.Chen G.Memik A.N.Choudhary S.Novakovic E.Bugnion S.Fytraki T.F.Wenisch K.Roy S.W.Kim C.Ooi R.Eigenmann J.C.Smolens B.T.Gold J.Kim J.C.Hoe A.Nowatzyk I.Schoinas A.R.Lebeck S.K.Reinhardt J.R.Larus M.L.Goodstein M.A.Kozuch S.Chen P.B.Gibbons T.C.Mowry R.Johnson N.Hardavellas I.Pandis N.Mancheril S.Harizopoulos K.Sabirli A.Ailamaki M.Sadrosadati A.Mirhosseini Seyed Borna Ehsani H.Sarbazi-Azad Mario Drumond R.Ausavarungnirun O.Mutlu Arash Pourhabibi Zarandi Siddharth Gupta Hussein Kassir Zilu Tian Mario Paulo Drumond Christoph Koch 0001 A.Adileh S.Volos M.Alisafaee D.Jevdjic C.Kaynak A.D.Popescu

Talks about:

parallel (4) scale (4) acceler (3) share (3) grain (3) out (3) submicron (2) processor (2) directori (2) communic (2)

Person: Babak Falsafi

DBLP: Falsafi:Babak

Contributed to:

2014

2013

2012

2011

2010

2009

2008

2007

2004

2002

2001

1999

1997

1994

2018

2019

2020

Wrote 21 papers:

ASPLOS-2014-NovakovicDBFG: Scale-out NUMA (SN, AD, EB, BF, BG), pp. 3–18.
HPCA-2014-FytrakiVKFG #monitoring #named #programmable: FADE: A programmable filtering accelerator for instruction-grain monitoring (SF, EV, YOK, BF, BG), pp. 108–119.
DATE-2013-CoppolaFGK #embedded #manycore: From embedded multi-core SoCs to scale-out processors (MC, BF, JG, GK), pp. 947–951.
ASPLOS-2012-FerdmanAKVAJKPAF #case study #hardware: Clearing the clouds: a study of emerging scale-out workloads on modern hardware (MF, AA, YOK, SV, MA, DJ, CK, ADP, AA, BF), pp. 37–48.
HPCA-2011-FerdmanLBF #manycore #scalability: Cuckoo directory: A scalable directory for many-core systems (MF, PLK, KB, BF), pp. 169–180.
ASPLOS-2010-VlachosGKCFGM #monitoring #named #online #parallel #thread: ParaLog: enabling and accelerating online parallel monitoring of multithreaded applications (EV, MLG, MAK, SC, BF, PBG, TCM), pp. 271–284.
HPCA-2009-WenischFAFM #memory management #metadata #streaming: Practical off-chip meta-data for temporal memory streaming (TFW, MF, AA, BF, AM), pp. 79–90.
ASPLOS-2008-BurceaSMF #predict: Predictor virtualization (IB, SS, AM, BF), pp. 157–167.
VLDB-2007-JohnsonHPMHSAF #question: To Share or Not To Share? (RJ, NH, IP, NM, SH, KS, AA, BF), pp. 351–362.
ASPLOS-2004-SmolensGKFHN #bound #detection #latency #named: Fingerprinting: bounding soft-error detection latency and bandwidth (JCS, BTG, JK, BF, JCH, AN), pp. 224–234.
HPCA-2004-ChenYFM #effectiveness #predict: Accurate and Complexity-Effective Spatial Pattern Prediction (CFC, SHY, BF, AM), pp. 276–287.
HPCA-2002-YangPFV #design #energy: Exploiting Choice in Resizable Cache Design to Optimize Deep-Submicron Processor Energy-Delay (SHY, MDP, BF, TNV), pp. 151–161.
HPCA-2001-MoshovosMFC #energy #named: JETTY: Filtering Snoops for Reduced Energy Consumption in SMP Servers (AM, GM, BF, ANC), pp. 85–96.
HPCA-2001-YangPFRV #approach #architecture: An Integrated Circuit/Architecture Approach to Reducing Leakage in Deep-Submicron High-Performance I-Caches (SHY, MDP, BF, KR, TNV), pp. 147–157.
PPoPP-2001-KimOEFV #analysis #execution #framework #optimisation: Reference idempotency analysis: a framework for optimizing speculative execution (SWK, ClO, RE, BF, TNV), pp. 2–11.
HPCA-1999-FalsafiW #abstraction #communication #parallel #programming #protocol #queue: Parallel Dispatch Queue: A Queue-Based Programming Abstraction to Parallelize Fine-Grain Communication Protocols (BF, DAW), pp. 182–192.
HPCA-1997-FalsafiW #communication #parallel #scheduling: Scheduling Communication on a SMP Node Parallel Machine (BF, DAW), pp. 128–138.
ASPLOS-1994-SchoinasFLRLW #data access #distributed #memory management: Fine-grain Access Control for Distributed Shared Memory (IS, BF, ARL, SKR, JRL, DAW), pp. 297–306.
ASPLOS-2018-SadrosadatiMESD #hardware #named: LTRF: Enabling High-Capacity Register Files for GPUs via Hardware/Software Cooperative Register Prefetching (MS, AM, SBE, HSA, MD, BF, RA, OM), pp. 489–502.
ASPLOS-2019-DaglisSF #named: RPCValet: NI-Driven Tail-Aware Balancing of µs-Scale RPCs (AD, MS, BF), pp. 35–48.
ASPLOS-2020-ZarandiGKSTDFK #data transformation: Optimus Prime: Accelerating Data Transformation in Servers (APZ, SG, HK, MS, ZT, MPD, BF, CK0), pp. 1203–1216.