Gilles F Nelon
email: é<gilles.fenelon@hmn.aphp.fr

Thierry Soulas

Laurent Cleret De Langavant

Iris Trinkler

Anne-Catherine Bachoud-L Vi

Feeling of presence in Parkinson s disease '

Background

A feeling of presence (FP), ie the vivid sensation that somebody (distinct from oneself) is present nearby, is commonly reported by patients with Parkinson s disease (PD) but its phenomenology has not been described precisely. The objective of this study was to ' provide a detailed description of FP in PD and to discuss its possible mechanisms.

Patients and methods

We studied 52 non-demented PD patients reporting FP in the preceding month (38 consecutive outpatients and 14 inpatients). FP characteristics were recorded with a structured questionnaire. The outpatients with FP were compared to 78 consecutive outpatients without FP.

Results

About half the patients said they recognized the identity of the presence. More than 75 of patients said the FP were not distressing, " " % were short-lasting, were felt beside and/or behind the patient, and occurred while indoors; most patients checked for a real presence but their insight was generally preserved. In 31 of cases the patients had an unformed visual hallucination simultaneously with the % FP. A higher daily levodopa-equivalent dose and the presence of visual illusions or hallucinations were independently associated with FP.

Discussion

Although FP is not a sensory perception, projection of the sensation into the extrapersonal space, along with the frequent co-occurrence of elementary visual hallucinations and the strong association with visual hallucinations or illusions, support its hallucinatory nature. FP may be viewed as a social hallucination, involving an area or network specifically activated when a living " "

being is present, independently of any perceptual clue.

INTRODUCTION

The feeling of presence (FP) refers to the vivid sensation that somebody (distinct from oneself) is present nearby, when no one is actually there, in the absence of sensory clues revealing a presence. Such sensations have given rise to numerous literary and religious accounts. The first description of FP by a psychologist was probably that of William James in 1902: "It often happens that an hallucination is imperfectly developed: the person affected will feel a presence in the room, definitely localized, ( ) and yet neither seen, heard, ' ' …

. Jaspers described the same phenomenon in 1913 under the name touched, nor cognized in any of the usual sensible ways ' ' " [START_REF] James | The varieties of religious experience. A study on human nature[END_REF] [2 ]

: leibhaftige Bewusstheit "There are patients who have a certain feeling (in the mental sense) or awareness that someone is close by, behind them or above them, someone that they can in no way perceive with the external senses, yet whose actual/concrete presence is

(translation by Koehler and Sauer

). Jaspers distinguished FP in normal subjects from those occurring in directly/clearly experienced " [3 ] patients with (ie schizophrenia) who lacked insight and incorporated the FP into a delusion. Critchley later identified dementia praecox [START_REF] Jaspers | ber leibhaftige Bewu theiten (Bewu theitsta schungen), ein psychopathologisches Elementarsymptom[END_REF] a variety of causes, including neurological conditions such as epilepsy, for this . This sensation has "sort of rudimentary hallucination " [4 ] been described as an idea, impression, sense or feeling of presence. The term extracampine hallucinations has been wrongly equated to " "

FP.

Bleuler called extracampine a type of visual or tactile hallucination reported by patients with psychiatric disorders and occurring

[5 ] " "

outside the limits of the corresponding sensory field. For example, a patient felt, on his skin, mice running on a wall, while another one [6 ] saw birds or persons in a garden while seated in a room with his back to the window. Thus, extracampine hallucinations have a sensory

" "
component that is typically absent in FP.

FP may be experienced by normal subjects, either without any facilitating factor, or more commonly following bereavement. About half of all persons who have lost their spouse report FP of the deceased in the years that follow.

There are also anecdotal reports of FP [7 ] occurring in extreme circumstances, for example during shipwrecks or high-altitude mountain climbing. FP are also experienced in [4 ] several pathological situations, including schizophrenia and schizotypal personality disorder , , Parkinson s disease (PD), , and To our knowledge, FP associated with PD was not described in the prelevodopa era. In the proceedings of a 1970 symposium, de Ajuriaguerra mentioned that patients with PD or post-encephalitic parkinsonism sometimes had the simple impression of a presence , but " "

he did not specify whether or not the patients received the recently available levodopa.

After dopaminergic treatment became

[23 ]
available, FP were recognized as common, and then systematically investigated in cross-sectional studies, along with hallucinations

[24 ]
and other minor psychotic symptoms of PD, such as visual illusions. , , FP is now accepted as part of the spectrum of psychotic phenomenology of FP has not yet been described systematically. The main goal of this study was therefore to provide a detailed description of FP in PD and, on the basis of its phenomenology, to start uncovering the possible mechanisms of this intriguing phenomenon.

METHODS

Subjects

Fifty-two PD patients who had experienced FP in the preceding month participated in the study. PD was diagnosed according to the UK Brain Bank criteria.

Patients had to be fluent in French and, if cognitively impaired, to be able to understand and answer the questionnaire. Patients were considered to have FP if they answered yes to the following question:

" " do you sometimes feel the presence of

"
The examiner made clear the difference between a formed visual hallucination (VH) of a person and an somebody when no-one is there? " FP. Thirty-eight of the 52 patients were identified among 116 consecutive outpatients, while the other 14 patients were inpatients. The 38 outpatients with FP were compared with the 78 patients from the same population who reported having no FP in the preceding month.

Procedures

To investigate the phenomenological characteristics of FP, we designed a structured questionnaire based on the general characteristics of hallucinatory phenomena in PD and on previous clinical experience. The questionnaire included 16 items distributed in 6 sections, [26 ] namely content, temporal characteristics, spatial characteristics, insight and repercussions, association with visual experience, and associated psychotic symptoms. Most of the items are self-explanatory, and some are commented on below. Insight was considered absent if the patient believed in the reality of a presence even after checking for and not finding a visible presence. The influence item explored

" "
the belief that the presence could influence the patient s thoughts or actions (excluding the brief action of checking for a real presence), by ' asking: do you think that the presence influences how you think or act? We had previously noticed that some patients reported a vague " " " "

visual impression concomitant with the sense of presence, and/or would spontaneously use terms of imagery in reporting their experience (e.g. I see a man behind me ). We therefore looked for elementary VH and, if present, ensured that they had none of the visual

" " [9 ]
characteristics of a person (recognizable features of a body, face or clothes). We also recorded the spontaneous use of imagery terms in the time frame of the questionnaire. The patients with FP (n 52) and the outpatients free of FP (n 77) also answered a previously published

= =
structured questionnaire on hallucinations in visual and other sensory modalities, visual illusions (ie the misinterpretation of a real external stimulus), and delusions. Their demographic and PD-related data were recorded. The levodopa-equivalent daily dose was calculated

[25 ]
using published equivalencies. The use of dopaminergic agonists, amantadine, anticholinergics, psychoactive drugs (antidepressants, II (BDI-II, maximum score 63, higher scores indicating more severe depressive symptoms). BDI-II scores were analyzed both as a

[30 ]

continuous variable and as a dichotomous variable, using a 19-point cut-off for clinical depression.

Statistical analysis

Fisher s two-tailed exact test and chi-squared test were used to examine the statistical significance of relations between categorical ' variables. When the whole cohort was divided into two samples on the basis of a categorical variable, independent tests were used to t compare the means of interval variables. Multivariate analysis used stepwise logistic regression and included all statistically significant covariates (p<0.05). Continuous variables were dichotomized around the median. SPSS 18.0 software for Windows was used for all analyses.

3 10

RESULTS

Characteristics of FP

The demographic and clinical characteristics of the 52 patients with FP are shown in , and the characteristics of the FP are Table 1 shown in . One patient felt the presence of a former pet dog, while all the other patients felt a human presence, which was Table 2 unidentified in most cases. Patients who felt the presence of a deceased relative were not more depressed than patients with other types of FP, as shown by the lack of difference between the two groups in the mean BDI-II scores (respectively 21.0 and 21.2, t(46) 0.08, = p = 0.932) and in the proportion of patients with scores higher than 19 (51 vs 69 , 0.338).

% % p =

In a few cases the presence was that of a close relative (commonly the spouse) who had just left the room, leaving the patient alone. More commonly the FP occurred while the patient was alone, but in circumstances in which he or she used to being in the company of the spouse; for example, while sitting on a sofa watching television, the patient would feel the presence of the spouse beside him/her. There was no predominant schedule in most cases. In only 3 cases was the FP clearly hypnagogic or hypnopompic, with no associated sleep paralysis. In about 80 of cases the sensation was brief (lasting a few seconds) and recurred more than once a week. FP had been present % for a mean of 2.9 4.2 years, but the patients were vague about the onset of the phenomenon.

±

In 58 of cases the presence was felt beside (and often slightly behind) the patient, as frequently on one side as on the other. Patients % who felt the presence beside or behind them felt it in close proximity. However, in 6 cases the presence was felt as remote, outside the house in one case and in another room in 5 cases. In the 47 patients in whom the FP tended to predominate on one side, there was no association between the side of the presence and the predominant side of motor signs ( 0.335, Fisher s exact test). The FP was often p = ' spontaneously described as static; none of the patients mentioned a moving presence.

Insight was preserved in 77 of cases. Compared with patients with preserved insight, patients with a lack of insight had a higher occasionally by scanning the room more intently. One patient occasionally woke his wife when he felt a presence outdoors. The phenomenon was described as unpleasant or worrisome in 38 of cases, but only four patients (8 ) said they felt really scared or % % threatened. Conversely, four patients, all of whom felt the presence of a relative (deceased in three cases), described the FP as pleasant, and even protective in two cases.

Few patients spontaneously used terms of imagery to describe the FP. However, nearly one-third said they saw an unformed shadow

" "
or mist associated with the sense of presence. This shadow never took the form of a human body or part of a body. For example, a

" " 64-year-old woman who had had PD for 16 years felt the presence of her beloved deceased grandmother; she saw, on her left side, " something like a shadow, a dense steam, a large rectangle with no head, no body and no feet but trying to look at me, turning towards me .

"

She would feel scared and look away.

Associated symptoms

FP was commonly associated with other non concomitant psychotic symptoms, including visual illusions, hallucinations (mostly formed VH), and occasionally delusions. One patient described formed VH and FP with similar characteristics. This 65-year-old man had had PD for 8 years and had moderate cognitive impairment. Sometimes he experienced a VH of a woman, whom he saw distinctly from head to foot, and at other times he felt the presence of a woman but had no accompanying visual sensation. In both cases he referred to an unidentified woman on his right side, and felt the need to check for a real presence by turning his head, which caused the phenomenon to cease. His VH occurred electively in the morning, while washing or shaving, while the FP occurred only at sleep onset during an afternoon nap. Patients with associated hallucinations had lower cognitive scores on the MMP than patients who had FP alone or combined with another minor psychotic symptom (respectively 24.2 and 27.4, (50) 3.24, 0.002). Patients with associated hallucinations also had a t = p = longer mean disease duration (13.0 and 9.2 y, (50) 2.10, 0.04). In contrast, they did not differ in terms of the BDI score, the mean t = p = L-dopa equivalent daily dose, or the use of psychoactive drugs.

Comparison of patients with and without FP

We then compared the demographic and clinical characteristics of the consecutive unselected outpatients with FP (n 38) and without = FP (n 78). Not all the patients without FP completed the MMP and BDI-II, and the results of these tests were therefore not included in this = analysis. The characteristics of the two groups are shown in . Multivariate analysis identified three independent factors predictive Table 3 of FP: higher levodopa-equivalent daily doses (>750 mg), VH, and visual illusions (

). We found no link between the predominant Table 4 side of parkinsonism and the existence of FP. We also compared the 15 outpatients with isolated FP, i.e. without visual illusions, hallucinations or delusions, with the 53 outpatients who had no psychotic symptoms. No significant differences were found (data not shown), but the patients with isolated FP tended to have higher levodopa-equivalent daily doses (898 vs 661 mg, p 0.053) and more = frequent use of psychoactive drugs (8 vs 13 patients, p 0.055).

=

DISCUSSION

Phenomenology of FP

This study provides the first clinical description of FP associated with PD. The characteristics of FP show some variability. The " identity of the presence was not always recognized. The emotional experience of FP was variable from one patient to another: FP was " occasionally unpleasant but rarely distressing. No predominant schedule was identified. However, the following characteristics were present in at least three-quarters of the patients: FP was short-lived (seconds) and occurred several times per week, indoors; the presence " "

was felt beside and/or behind the patient; the patient felt the need to check for a real presence but insight was preserved in most cases.

Even with lost insight, FP in PD patients typically lacked the delusional component characteristic of schizophrenia or other psychotic disorders. , When the FP was located beside the patient, there was no predominant side and no association the side of the

[2 8 ]
presence and the predominant side of PD motor signs, suggesting that hemispheric specialization plays no part in the genesis of FP in this setting. This contrasts with the previous findings of Persinger, who found that 22 of 28 patients reporting FP after closed head injury felt the presence on their left. Conversely, Brugger ., in a review of 27 cases of FP secondary to various causes, found a slight Two clinical characteristics of FP observed here have not previously been described. The first is the feeling of a persistent or recurrent presence of a person who had just left the scene. We propose to call this phenomenon , from the Greek , again , and palinparousia palin " "

, presence , by analogy with palinopsia. The temporal variety of palinopsia consists of the persistence, or the reappearance after parousia " " " "

a few seconds or minutes, of the image of an object after the subject has stopped looking at the object. Another interesting feature of

[31 ]
FP is the presence, in about one-third of cases, of an unformed VH which, although it has no recognizable human visual features, is associated with the FP, suggesting in these cases the activation of a neural network involving visual areas.

Factors associated with FP

PD patients with and without FP could not be compared for cognitive (MMP) and depression (BDI-II) scores. Despite this limitation, we identified some factors relevant to the discussion of the pathophysiology of FP. A higher daily levodopa-equivalent dose emerged as an independent predictor of FP. In contrast, in most previous studies the mean levodopa or levodopa-equivalent dose did not differ between patients with and without VH, suggesting a specific facilitating role of dopaminergic therapy in FP. Besides, visual illusions and VH [32 ] were independently predictive of FP, suggesting shared mechanisms (see below).

FP as a hallucinatory phenomenon

Our phenomenological data provide some insights into the nature of FP in PD, which we view as a hallucinatory phenomenon. Hallucinations have received a number of definitions, most of them referring to sensory experiences.

However, the concept of

[33 ]
non-sensory hallucinations was forwarded at the end of the nineteenth century, and, more recently, Nielsen took FP as an example to stress that an image was not mandatory to consider an experience as a hallucination.

A FP shares with hallucinations the vividity of the between heautoscopy ("a special type of autoscopic hallucination involving, along with the experience of seeing oneself, the somaesthetic

) and FP, such as a frequent feeling of familiarity or of close psychological affinity with the awareness of the presence of one s double ' "

presence; a distinct and specific distance from the person s body and the possible imitation of all body movements; and cases in which ' heautoscopy and FP are experienced in close temporal succession.

Could the FP in PD result from projection of the self into the extrapersonal space? Such a mechanism is unlikely for several reasons.

First, in 44 of cases the presence was identified as that of a precise relative, and, when the presence was unidentified, the patients never % reported a feeling of familiarity. Second, the FP occasionally started when the relative left the patient s presence, indicating an external ' trigger. Third, although the presence was usually felt in the patient s close vicinity, it was sometimes located in another room or outside the ' house. Fourth, in one case the FP was that of a dog, which is hardly consistent with an illusory self. Finally, FP in our PD patients was never associated with autoscopic hallucinations, and we are unaware of any reports of autoscopic phenomena in PD.

We therefore consider that FP in PD patients corresponds to the perception of a person distinct from oneself. This view is in line with that of Nielsen concerning FP associated with sleep paralysis attacks, and with that of Picard who reported on a patient with FP of

[22 ]
several familiar persons during a simple focal epileptic seizure.

There is extensive evidence that selective cortical regions are active

[17 ]
during the perception of biological forms and the perception of biological motion. Specific areas of the visual extrastriate cortex respond selectively to faces (e.g. the fusiform face area ) or to the rest of the human body , while other areas of the superior temporal sulcus

[37 ] [38 ]
region are activated by movements of the eyes, mouth, hands and body, and by static images of the face and body of implied motion.

[39 ]

However, it is unlikely that FP results primarily from activation of these areas. For example, abnormal activation of the fusiform face area is associated with hallucinatory perception of a face and not with a felt presence FP could involve another area or network that is

[40 ]
specifically activated when a person (or pet), but not an object, is present, independently of any perceptual clues to this presence. The frequent familiarity of the living being whose presence is felt, and the high prevalence of FP following bereavement, point to a connection between this putative area and both affective and autobiographical memory networks. FP can also be modulated by prior knowledge and perceptual expectation, as exemplified by the phenomenon of palinparousia. As a result, FP may be viewed as a social hallucination. 3 . Koehler K , Sauer H . Jasper s sense of presence in the light of Huber s basic symptoms and DSM-III ' '

. Compr Psychiatry . 1984 ;25 : 183 -191 4 . Critchley M . The idea of presence . 34 . Fish DR , Gloor FL , Quesney FL , Olivier A . Clinical responses to electrical brain stimulation of the temporal and frontal lobes in patients with epilepsy . Brain . 1993 ; 116 : 397

(10)

Spatial characteristics

Location of the presence

  /or hypnotics) and clozapine was recorded. Patients with FP completed a brief cognitive test, the Mini Mental Parkinson (MMP, maximum score 32, lower scores indicating poorer cognitive status) , and the French version of the Beck Depression Inventory

  right side.[19 ]

  -414 35 . Arzy S , Seeck M , Ortigue S , Spinelli L , Blanke O . Induction of an illusory shadow person . Nature . 2006 ; 443 : 287 - 36 . Dening TR , Berrios GE . Autoscopic phenomena . Br J Psychiatry . 1994 ; 165 : 808 -817 37 . Kanwisher N , Yovel G . The fusiform face area: a cortical region specialized fort the perception of faces . Phil Trans R Soc B . 2006 ; 361 : 2109 -2128 38 . Downing PE , Jiang Y , Shuman M , Kanwisher N . A cortical area selective for visual processing of the human body . Science . 2001 ; 293 : 2470 -2473 39 . Allison T , Puce A , McCarthy G . Social perception from visual cues: role of the STS region . Trends Cog Sci . 2000 ; 4 : 267 -278 40 . ffytche DH , Howard RJ , Brammer MJ , David A , Woodruff P , Williams S . The anatomy of conscious vision: an fMRI study of VHs . Nature Neurosci . 1998 ; 1 : 738 - Link with fluctuations Present in off state " "

  common form of hypnagogic and hypnopompic hallucination, whether it occurs in normal subjects or in the course of narcolepsy, and whether in isolation or simultaneously with sleep paralysis.[20 -22 ]

			"		" [3 8 ]	'		[9 10 ]
	dementia with Lewy bodies.	, [11 12 ]	FP may also occur as an epileptic aura,	[13 -17 ]	or following brain damage.	, [18 19 ]	Finally, FP is a

  symptoms in PD and is included in the new diagnostic criteria for PD-associated psychosis proposed by an NINDS-NIMH work group.[26 On applying these criteria to 116 consecutive patients with PD, we found that FP was experienced by 34 of patients and was the most

	"	"				[9 10 25 ]
	]					%
	prevalent psychotic symptom.	[25 ]	Similarly, Williams	et al.	recorded FP in 40 of 115 consecutive PD patients. %	[10 ]	However, the

  sensation and a projection into the extracorporeal space, with precise spatial features in most cases. Moreover, in our study, patients with FP were more likely than patients without FP to have visual illusions and VH. Further evidence of a hallucinatory mechanism is the concomitant presence of unformed VH in about one-third of our patients, the sense of presence being bound to the elementary VH.What could be the neural basis for FP? Studies of epileptic subjects show that FP may result from abnormal activation of specific cortical areas. FP, in most cases associated with fear, may occur in partial epileptic seizures originating in the temporal lobe on either side [

	"	"			[22 ]
						"
	Interestingly, experiences following bereavement include FP of the deceased (the most common type) as well as visual or auditory
	hallucinations (reviewed in ref	32	, p.67 68). Finally, in a factor analysis of psychotic symptoms of dementia with Lewy bodies, VH of -
	persons and FP were included in the same factor.[12 ]
	13 -17 ]	. Moreover, electrical brain stimulation during presurgical assessment of patients with medically intractable partial epilepsy may
	elicit FP.	, [16 34 35 ] ,	Arzy	et al	. found that stimulation of an area at the left temporo-parietal junction during preoperative assessment of
	a young woman with epilepsy induced an illusory shadow person which the patient felt very close and mimicked her body posture and

" "

position.

The authors suggested that the patient was experiencing a perception of her own body due to multisensory and/or [35 ] sensorimotor disintegration. A similar experience was elicited by stimulation of the left temporo-parieto-occipital junction in another patient with temporal lobe seizures. Interpretation of FP as an externally projected self is in line with previous descriptions of the FP [16 ] as a non-visual autoscopy . Brugger , in a review of FP after brain damage, emphasized the phenomenological similarities " " [36 ] et al. [19 ]

  Mahieux F , Michelet D , Manifacier MJ , Boller F , Fermanian J , Guillard A . Mini-mental Parkinson: first validation study of a new bedside test constructed for Parkinson s disease ' . Behav Neurol . 1995 ; 8 : 15 -22 30 . Beck AT , Steer RA , Brown GK . Manual for the Beck Depression Inventory . 2 San Antonio The Psychological Corporation ; 1996 ; 31 . ffytche DH , Howard RJ . The perceptual consequences of visual loss: positive pathologies of vision Stebbins G , Goetz CG . Hallucinations in Parkinson disease . Nature Rev Neurol . 2009 ; 5 : 331 -342 33 . Aleman A , Lar i ø F . Hallucinations. The science of idiosyncratic perception . Washington American Psychological Association ; 2008 ;

	29 . "	"	. Brain . 1999 ; 122 : 1247 -1260
	32 . Diederich NJ , F nelon
			Acta Psychiatr Neurol Scand . 1955 ; 30 : 155 -168
	5 . Sato Y , Berrios GE . Extracampine hallucinations . Lancet . 2003 ; 361 : 1479 -1480
	6 . Bleuler E . Extracampine Hallucinationen . Psychiatrisch-Neurologische Wochenschrift . 1903 ; 25 : 261 -264
	7 . Grimby A . Bereavement among elderly people: grief reactions, post-bereavement hallucinations and quality of life . Acta Psychiatr Scand . 1993 ; 87 : 72 -80
	8 . American Psychiatric Association . Diagnostic and statistical manual of mental disorders . 4 (DSM IV) Washington, DC American Psychiatric Association ; 1994 ;
	9 . F nelon é	G , Mahieux F , Huon R , Zi gler é	M . Hallucinations in Parkinson s disease. Prevalence, phenomenology and risk factors '	. Brain . 2000 ; 123 : 733 -745
	10 . Williams DR , Warren JD , Lees AJ . Using the presence of visual hallucinations to differentiate Parkinson s disease from atypical parkinsonism '	. J Neurol Neurosurg
	Psychiatry . 2008 ; 79 : 652 -655
	11 . Chan D , Rossor MN . -but who is that on the other side of you? Extracampine hallucinations revisited " "	. Lancet . 2002 ; 360 : 2064 -2066
	12 . Nagahama Y , Okina T , Suzuki N , Matsuda M . Neural correlates of psychotic symptoms in dementia with Lewy bodies . Brain . 2010 ; 133 : 557 -567
	13 . Ardila A , G mez ó	J . Paroxysmal feeling of somebody being nearby "	" . Epilepsia . 1988 ; 29 : 188 -189
	14 . Landtblom A-M . The sensed presence : an epileptic aura with religious overtones " "	. Epilepsy Behav . 2006 ; 9 : 186 -188
	15 . Biraben A , Taussig D , Thomas P . Fear as the main feature of epileptic seizures . J Neurol Neurosurg Psychiatry . 2001 ; 70 : 186 -191
	16 . Zijlmans M , van Eijsden P , Ferrier CH , Kho KH , van Rijen PC , Leitjen FSS . Illusory shadow person causing paradoxical gaze deviations during temporal lobe
	seizures . J Neurol Neurosurg Psychiatry . 2009 ; 80 : 686 -688
	17 . Picard F . Eplileptic feeling of multiple presences in the frontal space . Cortex . 2010 ; 46 : 1037 -1042
	18 . Persinger MA . Sense of presence and suicidal ideation following traumatic brain injury: indications of right-hemispheric intrusions from neuropsychological profiles .
	Psychol Rep . 1994 ; 75 : 1059 -1070
	19 . Brugger P , Regard M , Landis T . Unilaterally felt presences : the neuropsychiatry of one s invisible doppelganger " " ' " " . Neuropsychiatry Neuropsychol Behav Neurol .
	1996 ; 9 : 114 -122
	20 . Ribstein M . Editor: Guilleminault C , Dement WC , Passouant P . Hypnagogic hallucinations . Narcolepsy . New-York Spectrum Publications ; 1976 ; 145 -160
	21 . Cheyne JA , Girard TA . Paranoid delusions and threatening hallucinations: a prospective study of sleep paralysis experiences . Conscious Cogn . 2007 ; 16 : 959 -974
	22 . Nielsen T . Felt presence: paranoid delusion or hallucinatory imagery . Conscious Cogn . 2007 ; 16 : 975 -983
	23 . 6 10

De Ajuriaguerra . Editor: de Ajuriaguerra J , Gauthier G . Etude psychopathologique des parkinsoniens . Monoamines, noyaux gris centraux et syndrome de Parkinson .

Paris Georg, Gen ve, Masson

è ; 1971 ; 327 -351 24 . Sanchez-Ramos JR , Ortoll R , Paulson GW . Visual hallucinations associated with Parkinson disease . Arch Neurol . 1996 ; 53 : 1265 -1268 25 . F nelon é G , Soulas T , Zenasni F , Cleret de Langavant L . The changing face of Parkinson s disease-associated psychosis: a cross-sectional study based on the new ' NINDS-NIMH criteria . Mov Disord . 2010 ; 25 : 763 -766 26 . Ravina B , Marder K , Fernandez HH . Diagnostic Criteria for Psychosis in Parkinson s disease: Report of an NINDS/NIMH Work Group ' . Mov Disord . 2007 ; 22 : 1061 -1068 27 . Gibb WRG , Lees AJ . The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson s disease ' . J Neurol Neurosurg Psychiatry . 1988 ; 51 : 745 -752 28 . Thobois S . Proposed dose equivalence for rapid switch between dopamine receptor agonists in Parkinson s disease: a review of the literature ' . Clin Ther . 2006 ; 28 : 1 -é G ,

10

10

10

10

Acknowledgements:

We are grateful to Dr l onore Bayen for translating Jasper s article from the German and to David Young for editing the manuscript.

É é '

Footnotes:

Competing interests None


André Seznec

A 64 Kbytes ISL-TAGE branch predictor *

Outline

The ISL-TAGE predictor consists in a TAGE predictor combined with a loop predictor (to predict loops) , a Statistical Corrector predictor and an Immediate Update Mimicker, IUM.

A TAGE predictor [START_REF] Seznec | A case for (partially)-tagged geometric history length predictors[END_REF] constitutes the core of the ISL-TAGE predictor.

The TAGE predictor (Section 2) captures most of the correlation on the branch outcomes for very long histories. But sometimes TAGE fails to predict loops with constant number of iterations. The loop predictor (Section 3 ) is used to predict these loops. TAGE also fails to predict branches that are not strongly correlated, but only statistically biased. The Statistical Corrector predictor (Section 4) is in in charge of tracking these statistically correlated branches that are not correctly predicted by the TAGE predictor. The TAGE predictor must be updated at retire time to avoid pollution by the wrong path; this delayed update induces extra mispredictions compared with an optimistic at fetch time update. The Immediate Update Mimicker (Section 5) aims at limiting these extra mispredictions through predicting branches with inflight non-retired occurrences.

The parameters of the submitted ISL-TAGE predictor are summarized in Section 6 . [START_REF] Seznec | Design tradeoffs for the ev8 branch predictor[END_REF] The TAGE conditional branch predictor

The TAGE predictor was described in [START_REF] Seznec | The l-tage branch predictor[END_REF] and [START_REF] Seznec | A case for (partially)-tagged geometric history length predictors[END_REF]. Only marginal modification sare introduced here, essentially associated with the huge storage budget allowed for the contest.

Figure 1 illustrates a TAGE predictor. The TAGE predictor features a base predictor T0 in charge of providing a basic prediction and a set of (partially) tagged predictor components Ti. These tagged predictor components Ti, 1 ≤ i ≤ M are indexed using different history lengths that form a geometric series [START_REF] Seznec | Analysis of the o-gehl branch predictor[END_REF], i.e, L(i) = (int)(α i-1 * L(1) + 0.5). Throughout this paper, the base predictor will be a simple PC-indexed 2-bit counter bimodal table; in order to save storage space, the hysteresis bit is shared among several counters as in [START_REF] Seznec | Design tradeoffs for the ev8 branch predictor[END_REF]. An entry in a tagged component consists in a signed counter ctr which sign provides the prediction, a (partial) tag and an unsigned useful counter u. Throughout this paper, u is a 1-bit counter and ctr is a 3-bit counter.

Sharing storage space between predictor tables in the TAGE predictor The TAGE predictor features independent logic tables. For some applications, some of the tables are underutilized while some others are under larger pressure. Sharing the storage space among several tables can be implemented without requiring to a real multiported memory table, but a bank interleaved tables as illus-trated in Figure 1. Experiments showed that global interleaving of all tables is not the best solution, but that interleaving between for a few adjacent history lengths can be slightly beneficial (reduction of about 1% of the misprediction number on the distributed benchmark sets).

A few definitions and notations The provider component is the matching component with the longest history. The alternate prediction altpred is the prediction that would have occurred if there had been a miss on the provider component.

If there is no hitting component then altpred is the default prediction.

Prediction computation

The prediction selection algorithm is exactly the same in [START_REF] Seznec | The l-tage branch predictor[END_REF] or [START_REF] Seznec | A case for (partially)-tagged geometric history length predictors[END_REF].

At prediction time, the base predictor and the tagged components are accessed simultaneously. The prediction is provided by the hitting tagged predictor component that uses the longest history. In case of no matching tagged predictor component, the default prediction is used.

However we remarked that when the confidence counter of the matching entry is null, on some traces, the alternate prediction altpred is sometimes more accurate than the "normal" prediction. This property is global to the application and can be dynamically monitored through a single 4-bit counter ( USE ALT ON NA in the simulator).

Prediction computation summary Therefore the prediction computation algorithm is as follows:

1. Find the longest matching component and the alternate component 2. if (the confidence counter is not weak or USE ALT ON NA is negative) then the provider component provides the prediction else the prediction is provided by the alternate component

Updating the TAGE predictor

Update on a correct prediction by the longest marching entry The prediction counter of the provider component is updated.

Update on a misprediction by the longest matching entry

First we update the provider component prediction counter.

As a second step, if the provider component Ti is not the component using the longest history (i.e., i < M ) , we try to allocate entries on predictor components Tk using a longer history than Ti (i.e., i < k < M ).

It should be noticed that, since, the predictor size storage budget allocated for the competition is huge we allocate up to 4 of these entries. For smaller predictors, one would try to limit the footprint of the application on the predictor by allocating a single predictor entry. The M-i-1 u j useful bits are read from predictor components Tj, i < j < M . The allocation algorithm chose up to four entries for which the useful bits are null, moreover we guarantee that the entries are not allocated in consecutive tables. When an entry is allocated, its prediction counter is set in weak mode and its useful bit is set to null.

Updating the useful bit u The useful bit u of the provider component is set whenever the actual prediction is correct and the alternate prediction altpred is incorrect.

In order to avoid the useful bits to stay forever set, we implement the following reset policy. On allocation of new entries, we dynamically monitor the number of successes and fails when trying to allocate new entries after a misprediction; this monitoring is performed through a single 8-bit counter (u=1, increment, u=0 decrement). This counter (variable TICK in the simulator) saturates when more failures than successes are encountered on allocations. At that time we reset all the u bits of the predictor. Typically, such a global reset occurs when one of two entries on the used portion of the predictor has been set to useful. This simple policy was found to be more efficient than the previously proposed management using 2-bit useful counters for the TAGE predictor [START_REF] Seznec | A case for (partially)-tagged geometric history length predictors[END_REF][3].

The loop predictor component

The loop predictor simply tries to identify regular loops with constant number of iterations.

The implemented loop predictor provides the global prediction when a loop has successively been executed 7 times with the same number of iterations. The loop predictor used in the submission features only 64 entries and is 4-way skewed associative.

Each entry consists of a past iteration count on 10 bits, a speculative and a retire iteration count on 10 bits each , a partial tag on 10 bits, a confidence counter on 3 bits, an age counter on 3 bits and 1 direction bit i.e. 47 bits per entry. The loop predictor storage is only 3,008 bits i.e. 376 bytes.

Replacement policy is based on the age. An entry can be replaced only if its age counter is null. On allocation, age is first set to 7. Age is decremented whenever the entry was a possible replacement target and incremented when the entry is used and has provided a valid prediction. Age is reset to zero whenever the branch is determined as not being a regular loop.

The Statistical Corrector Predictor

The TAGE predictor is very efficient at predicting very correlated branches even if the correlation is with very remote branches, e.g. on a 1000 bits branch history. However TAGE fails at predicting statistically biased branches e.g. branches that have only a very small bias towards a direction, but are not correlated to the history path. On some of these branches, the TAGE predictor performs worse than a simple PC-indexed table of wide counters.

In order to better predict this class of statistically biased branches, we introduce the Statistical Corrector predictor . The correction aims at detecting the unlikely predictions and to revert them: the prediction and the (address, history) pair is presented to Statistical Corrector predictor which decides whether or not inverting the prediction. Since in most cases the prediction provided by the TAGE predictor is correct, the Statistical Corrector predictor can be quite small.

In the submission, the Statistical Corrector predictor is derived from the GEHL predictor [START_REF] Seznec | Analysis of the o-gehl branch predictor[END_REF]. It features 5 logical tables indexed with the same history lengths as the main TAGE predictor (0, 3,8,12,17) and the prediction (taken/not taken) flowing out from the TAGE predictor. The logical tables are sharing a single interleaved 4K 6-bit entries, i.e., 3Kbytes. The prediction is computed as the sign of the sum of the (centered) predictions read on the Statistical Corrector table plus the (centered) output of the hitting bank in TAGE (x8), thus taking into account the confidence in the TAGE prediction. The TAGE prediction is reverted if the Statistical Corrector predictor disagrees and the absolute value of the sum is above a dynamic threshold. The dynamic threshold is adjusted at run-time in order to ensure that the use Statistical Corrector predictor is beneficial. The technique is similar to the technique used for dynamically adapting the update threshold of the GEHL predictor.

The Immediate Update Mimicker

On a real hardware processor, the predictor tables are updated at retire time to avoid pollution of the predictor by the wrong path. A single predictor table entry may provide several mispredictions in a row due to this late update. In order to reduce this impact, we implement an add-on to TAGE, the IUM, immediate update mimicker.

However on a misprediction the history can be repaired immediately and when a block is fetched on the correct path, the still speculative branch history is correct. In practice, repairing the global history is straightforward if one uses a circular buffer to implement the global history. We leverage the same idea with IUM predictor. When fetching a conditional branch, IUM memorizes the identity of the entry E in the TAGE predictor (number of the table and its index) that provides the prediction as well as the predicted direction. At branch resolution on a misprediction, the IUM is repaired through reinitializing its head pointer to the associated IUM entry and updating this entry with the correct direction.

When fetching on the correct path, the associated IUM entry associated with an inflight branch B features the matching predictor entry E that provided the TAGE prediction and the effective outcome of branch B (corrected in case of a misprediction on B). In case of a new hit on entry E in the predictor before the retirement of branch B, the (TAGE predictor + IUM) can respond with the direction provided by the IUM rather than with the TAGE prediction (on which entry E has not been updated).

IUM can be implemented in hardware through a fully-associative table, It allows to recover about 3/ 4th of the mispredictions due to late update of the TAGE predictor tables. The storage cost of the speculative predictor is only 64*20 bits, i.e. 160 bytes, plus the pointers to determine the head ( position of the last fetch branch) and the tail ( position of the next to be retired branch) of the IUM.

Important remark : In the submission, the TAGE predictor, the Statistical Predictor and the loop predictor are re-read at retire stage to recompute the predictions, but also to get parameters such as the provider components etc before update. On a real hardware predictor, one would like to avoid this re-read and recomputation. The IUM could be augmented with a few fields (counter values, u bit, ..) to transmit these informations from fetch stage to retire stage, thus saving an extra read on the predictor tables.

6 The submitted ISL-TAGE predictor

The TAGE predictor component

For a 512 Kbits predictor, the best accuracy we found is achieved by a 16 components TAGE predictor, i.e. 15 tagged components and a base bimodal predictor. Hysteresis bits are shared on the base predictor. Each entry in predictor table Ti features a Wi bits wide tag, a 3-bit prediction counter and a 1-bit useful counter.

Tag width tradeoff

Using a large tag width leads to waste part of the storage while using a too small tag width leads to false tag match detections. Experiments showed that one can use narrower tags on the tables with smaller history lengths.

The global history vector

The usual combination of the global branch history vector and a short path history (limited to 1 bit per branch) was found to be slightly outperformed by a global history vector introducing much more information for the indirect branches as well as for the calls. 4 bits (resp. 5 bits) mixing target and program counter are introduced for the indirect branches and the calls.

TAGE parameters

Since this is competition we have run a guided search for the best set of history lengths. We first determined the number and respective sizes of tables in the predictor through exploring the design space using series of geometric history lengths. Then we grouped the tables to be interleaved. This leads to a configuration with 4 groups of tagged tables with increasing tag width, respectively T1-T2, T3-T7, T8-T13 and T14-T15. The set of possible history lengths was then explored with a geometric series with minimum history length 8 and maximum history length 2000 as a starting point. The set of history lengths in the submitted predictor is {0, [START_REF] Seznec | The l-tage branch predictor[END_REF]8,12,17,33,35,67,97,138,195,330,517,1193,1741 Apart the prediction tables storage, the ISL-TAGE predictor uses 1) a circular buffer to store the history, for convenience we use a a 4Kbits circular buffer, 2) two 12-bit pointers on the circular buffer, one for fetch history, the second for retire history 3) two 16 bits path history vectors 4) a 7-bit counter to determine the usefulness 5) a 8-bit counter to control the u bits reset 6) a 32-bit random number 7) two 6-bit pointers on the IUM 8) two 6-bit counters to manage the threshold on the statistical corrector, i.e. a total of 4,223 extra storage bits for control logic.

In total, the ISL predictor uses 65,833bytes of storage.

7

Options of the submitted ISL-TAGE predictor Through commenting some #define lines, one can run different versions of the submitted predictor.

#define IUM enables the IUM predictor. #define INITHISTLENGTH enables the use of the best found set of history length. #define SHARINGTABLES enables the sharing of storage tables among the logic tables of the TAGE predictor. #define LOOPPRE-DICTOR enables the loop predictor. #define STAT-COR enables the Statistical Corrector predictor.

Figure 1 :

 1 Figure 1: A 4-component TAGE predictor synopsis: a base predictor is backed with several tagged predictor components indexed with increasing history lengths

Table 1 :

 1 Characteristics of the TAGE predictor components6.2.1 Total predictor storage budgetThe total storage budget for the submitted ISL-TAGE predictor represents 61,696 bytes for TAGE predictor, 3,072 bytes for the Statistical Corrector predictor, 376 bytes for the loop predictor and 160 bytes for the IUM predictor, i.e a total of 65,304 bytes.

					, 1930}.
	The characteristics of the TAGE component are
	summarized in Table 1. The base bimodal predictor
	features 32K prediction entries sharing 8K hysteresis
	entries. The TAGE predictor features a total of 482
	Kbits of prediction storage.
		Base	T1-2 T3-7 T8-13 T14-15
	Kentries 32+8	4	16	8	1
	Tag bits		8	11	13	14
	Kbits	40	48	240	136	18

This work was partially supported by the European Research Council Advanced Grant DAL


André Seznec

A 64-Kbytes ITTAGE indirect branch predictor *

The ITTAGE, Indirect Target TAgged GEometric length predictor, was introduced in [5] at the same time as the TAGE conditional branch predictor.

. It relies on (partial) match to select the predicted target of an indirect jump. TAGE also uses GEometric history length as the O-GEHL predictor [3], i.e. , the set of used global history lengths forms a geometric series. This allows to efficiently capture correlation on recent branch outcomes as well as on very old branches.

Due to the huge storage budget available for the ChampionShip, we propose an ITTAGE predictor featuring 16 prediction tables. On the distributed set of traces, using a path history vector recording only information from indirect jumps and calls was found to be (slightly) more efficient than using a path/branch history vector combining information from all kind of branches.

The ITTAGE indirect jump target predictor

Building on top of the cascaded predictor [START_REF] Driesen | The cascaded predictor: Economical and adaptive branch target prediction[END_REF] and on the TAGE predictor, the ITTAGE predictor was proposed in [START_REF] Seznec | The l-tage branch predictor[END_REF]. In this section, we recall the general principles of the ITTAGE indirect target predictor.equivalent storage budget. Some implementation details from the initial ITTAGE proposition are slightly modified in order to improve the global prediction accuracy.

ITTAGE predictor principles

ITTAGE relies on the same principles as the TAGE predictor several predictor tables indexed through independent functions of the global branch/path history and the branch address.

The Indirect Target TAgged GEometric length, ITTAGE, predictor features a tagless base predictor T0 in charge of providing a default prediction and a set of (partially) tagged predictor components. The tagged predictor components Ti, 1 ≤ i < M are indexed using different history lengths. The set of history lengths form an increasing series, i.e L(i) = (int)(α i-1 * L(1) + 0.5). This is illustrated in Figure 1. The counters representing predictions in TAGE are replaced by the target addresses Target . A predictor table entry also features a tag, a 2-bit confidence counter Ctr allowing some hysteresis on the predictor and a useful bit U for controlling the update policy ( Figure 2). A few definitions and notations In the remainder of the paper, we define the provider component as the predictor component that ultimately provides the prediction. We define the alternate prediction altpred as the prediction that would have occurred if there had been a miss on the provider component. That is, if there are tag hits on T2 and T4 and tag misses on T1 and T3, T4 is the provider component and T2 provides altpred. If there is no hitting component then altpred is the default prediction.

Prediction computation

The prediction selection algorithm is directly inherited from the TAGE predictor [START_REF] Seznec | The l-tage branch predictor[END_REF]. The optimization for weak counters entries proposed for TAGE (Section 3.2.4 [START_REF] Seznec | The l-tage branch predictor[END_REF]) is also implemented. At prediction time, the base predictor and the tagged components are accessed simultaneously. The prediction is provided by the hitting tagged predictor component that uses the longest history. In case of no matching tagged predictor component, the default prediction is used.

The optimization for weak confidence counters

We remarked that when the confidence counter of the matching entry is null, on some traces, the alternate prediction altpred is sometimes more accurate than the "normal" prediction. This property is global to the application and can be dynamically monitored through a single 4-bit counter (USE ALT ON NA in the simulator). On the distributed benchmark set, this optimization reduces the misprediction number by 2%.

Prediction computation summary Therefore the prediction computation algorithm is as follows: Update on a misprediction First we update the provider component entry. If the confidence counter is non-null then we decrement it. If the confidence counter is null then we replace the Target field in the predictor entry by the effective target of the branch. As a second step, if the provider component Ti is not the component using the longest history (i.e., i < M ) , we try to allocate entries on predictor components Tk using a longer history than Ti (i.e., i < k < M ). Since, the predictor size storage budget allocated for the competition is huge we allocate up to 3 of these entries. For smaller predictors, one would try to limit the footprint of the application on the predictor by allocating a single predictor entry.

The M-i-1 u j useful bits are read from predictor components Tj, i < j < M . The allocation algorithm chose up to four entries for which the useful bits are null, moreover we guarantee that the entries are not allocated in consecutive tables. On an allocated entry, the confidence counter is set to weak and the useful bit is set to null.

Updating the useful bit u The useful bit u of the provider component is set whenever the actual prediction is correct and the alternate prediction altpred is incorrect.

In order to avoid that useful bits stay forever set, we implement the following reset policy. On allocation of new entries, we dynamically monitor the number of successes and fails when trying to allocate new entries after a misprediction; this monitoring is performed through a single 8-bit counter (u=1, increment, u=0 decrement). This counter (variable TICK in the simulator) saturates when more fails than successes are encountered on updates. At that time we reset all the u bits of the predictor. Typically, such a global reset occurs when in average half of the entries on the used portion of the predictor has been set to useful. This simple policy was found to be more efficient than the previously proposed management for useful counters for the TAGE predictor [START_REF] Seznec | A case for (partially)-tagged geometric history length predictors[END_REF][4].

A few optimizations

The global history vector

The combination of the global branch history vector and a short path history (limited to 1 bit per branch) used in [START_REF] Seznec | A case for (partially)-tagged geometric history length predictors[END_REF] was found to be significantly outperformed by a global history vector introducing much more information for the indirect branches as well as for the calls. Respectively 10 bits and 5 bits mixing target and program counter are introduced for the indirect branches and the calls. This reduces the misprediction number by nearly 16 % compared with using a single (taken/not taken) bit for each branch. Experiments showed that using only path informations bits of indirect branches and calls results in better performance on the set of distributed traces than also incorporating information for the other branches.

However drawing conclusions from this experiment appears as really hazardous as the performance difference with using a global history vector where other branches are inserted as a single bit is marginal (about 3,000 mispredictions in total over the 40 distributed traces). It should be pointed out that, for the submitted predictor, three single indirect branches constitute a very significant fraction of

Leveraging target locality

The target field represents the major storage cost in a predictor entry. However branch targets exhibit some address locality. Exploiting such locality is not that simple since some of the benchmarks use targets scattered on more 1K 4Kbytes pages. However we found that all the benchmarks uses less than 128 256Kbytes. Therefore the Target field (32 bits) in a predictor entry is replaced by a Region offset (18 bits) and a Region pointer ( 7 bits), thus saving 7 bits on each entry (Figure 3). A 128-entry target region table must be added to rebuild the complete address, each entry featuring a 14-bit region address and a Useful bit for replacement. On a prediction, the target region table is only read at a given address. On a misprediction, the target region table is fully-associative searched for the matching region for the effective target; in case of a miss on the target region table, a target region entry is allocated.

The total storage for the target region

Miscelleanous optimizations

We present here two optimizations that are proposed for the ISL-TAGE predictor for the companion conditional predictor contest. We have implemented them in the submitted predictor, but that do not bring very significant benefit: in total they reduce the misprediction number by less than 1 %.

Sharing storage space between predictor tables

As represented on Figure 1, ITTAGE predictor features independent tables. For some applications, some of the tables are underutilized while some others are under large pressure. Sharing the storage space among several tables can be implemented without requiring to a real multiported memory table, but a bank interleaved table. E.g on Figure 4, T1. T2, and T3 are grouped in a 4-way interleaved table, history vector of length L( 1) is hashed to determine the bank that will deliver prediction for T1, prediction for T2 is delivered by the adjacent bank , etc,. Experiments showed that global interleaving of all tables is not the best solution, but that interleaving between for a few adjacent history lengths can be beneficial.

Groups

T0 T1-T2 T3-T10 T11-T15 On a real hardware processor, the predictor tables are updated at retire time to avoid pollution of the predictor by the wrong path. A single predictor table entry may provide several mispredictions in a row due to this late update. In order to reduce this impact, we implement an add-on to TAGE, the IUM, immediate update mimicker.

However on a misprediction the history can be repaired immediately and when a block is fetched on the correct path, the still speculative branch history is correct. In practice, repairing the global history is straightforward if one uses a circular buffer to implement the global history. We leverage the same idea with IUM predictor. When fetching an indirect branch, IUM memorizes the identity of the entry E in the ITTAGE predictor (number of the table and its index) that provides the prediction as well as the predicted direction. At branch resolution on a misprediction, the IUM is repaired through reinitializing its head pointer to the associated IUM entry and updating this entry with the correct target.

When fetching on the correct path, the associated IUM entry associated with an inflight branch B features the matching predictor entry E that provided the ITTAGE prediction and the effective target of branch B (corrected in case of a misprediction on B). In case of a new hit on entry E in the predictor before the retirement of branch B, the (ITTAGE predictor + IUM) can respond with the direction provided by the IUM rather than with the ITTAGE prediction (on which entry E has not been updated).

IUM can be implemented in hardware through a fully-associative table, It allows to recover about 3/ 4th of the mispredictions due to late update of the IT-TAGE predictor tables. The storage cost of the speculative predictor is only 64*48 bits, i.e. 384 bytes, plus the pointers to determine the head ( position of the last fetch branch) and the tail ( position of the next to be retired branch) of the IUM.

The submitted predictor characteristics

The characteristics of the submitted are summarized in Table 1. Both Tables T0 and T1 are directly indexed with the program counter since some of the benchmarks feature a huge number of static indirect branches and it appeared that the performance of the predictor on those benchmarks might have been impaired by conflicts on T0. T0 does not feature tags and u bits.

We have chosen a guided search of the best set of history lengths. Using a geometric series with minimum history length 8 and maximum history length 2000, we first determined the number of tables (16), their grouping, their respective sizes and their tag widths. Table T0 is not shared. Tables T1 andT2 form a first sharing group. T3 to T10 form a second sharing group and T11 to T15 form the last group. The set of possible history lengths was then explored with the geometric series as the starting point. The set of history lengths in the submitted predictor is {0, 0, 10, 16, 27, 44, 60, 96, 109, 219, 449, 487, 714, 1313, 2146, 3881}. These characteristics are summarized in Table 1.

The storage cost of the predictor consists in a total of 506Kbits of storage for the ITTAGE predictor tables, 240 bytes for the target region table, 384 bytes for IUM, i.e. a total of 65,392 bytes of storage for predictions and target regions.

The storage needed for the extra logic consists of a circular buffer of for storing the history bits (for simplifying the code, we use a 4Kbits buffer), two 12bit pointer on this buffer for respectively speculative history and retire history, a 32-bit register for pseudorandom value computed on the fly, a 8-bit counter to control the reset of the u bits, a 4-bit counter to control the possible use of the alternate prediction, two 6-bit pointers on the IUM i.e a total of 4176 bits of extra storage for the history and control logic.

Options of the submitted ITTAGE predictor

Through commenting some #define lines, one can run different versions of the submitted predictor.

_ #define IUM enables the IUM predictor. #define INITHISTLENGTH enables the use of the best found set of history length.

#define SHARINGTABLES enables the sharing of storage tables among the logic tables of the ITTAGE predictor.

Figure 2 :

 2 Figure 1: The Indirect Target TAgged GEometric length, ITTAGE, predictor

  the mispredictions: two branches common to traces INT05 and INT06 (which are traces from the same application) and aone branch from SERVER01. The two branches from INT05 and INT06 are better predicted by the history vector combining only indirect branches and calls. Discounting INT05 and INT06 (or even only one of them) would have pushed to use the more conventional history including all branches.

Figure 3 :

 3 Figure 3: Exploiting indirect target locality for 64-bit architecture the use of indirect access to target region table would allow to nearly halves the total storage size of the predictor.

Figure 4 :

 4 Figure 4: Sharing storage space between predictor tables

Table 1 :

 1 Characteristics of the tables of the ITTAGE predictor

	Total

This work was partially supported by the European Research Counsil Advanced Grant DAL