You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


/*
 * SN Platform GRU Driver
 *
 * 		MMUOPS callbacks  + TLB flushing
 *
 * This file handles emu notifier callbacks from the core kernel. The callbacks
 * are used to update the TLB in the GRU as a result of changes in the
 * state of a process address space. This file also handles TLB invalidates
 * from the GRU driver.
 *
 *  Copyright (c) 2008 Silicon Graphics, Inc.  All Rights Reserved.
 *
 *  This program is free software; you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation; either version 2 of the License, or
 *  (at your option) any later version.
 *
 *  This program is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with this program; if not, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA
 */

#include <linux/kernel.h>
#include <linux/list.h>
#include <linux/spinlock.h>
#include <linux/mm.h>
#include <linux/slab.h>
#include <linux/device.h>
#include <linux/hugetlb.h>
#include <linux/delay.h>
#include <linux/timex.h>
#include <linux/srcu.h>
#include <asm/processor.h>
#include "gru.h"
#include "grutables.h"
#include <asm/uv/uv_hub.h>

#define gru_random()	get_cycles()

/* ---------------------------------- TLB Invalidation functions --------
 * get_tgh_handle
 *
 * Find a TGH to use for issuing a TLB invalidate. For GRUs that are on the
 * local blade, use a fixed TGH that is a function of the blade-local cpu
 * number. Normally, this TGH is private to the cpu & no contention occurs for
 * the TGH. For offblade GRUs, select a random TGH in the range above the
 * private TGHs. A spinlock is required to access this TGH & the lock must be
 * released when the invalidate is completes. This sucks, but it is the best we
 * can do.
 *
 * Note that the spinlock is IN the TGH handle so locking does not involve
 * additional cache lines.
 *
 */
static inline int get_off_blade_tgh(struct gru_state *gru)
{
	int n;

	n = GRU_NUM_TGH - gru->gs_tgh_first_remote;
	n = gru_random() % n;
	n += gru->gs_tgh_first_remote;
	return n;
}

static inline int get_on_blade_tgh(struct gru_state *gru)
{
	return uv_blade_processor_id() >> gru->gs_tgh_local_shift;
}

static struct gru_tlb_global_handle *get_lock_tgh_handle(struct gru_state
							 *gru)
{
	struct gru_tlb_global_handle *tgh;
	int n;

	preempt_disable();
	if (uv_numa_blade_id() == gru->gs_blade_id)
		n = get_on_blade_tgh(gru);
	else
		n = get_off_blade_tgh(gru);
	tgh = get_tgh_by_index(gru, n);
	lock_tgh_handle(tgh);

	return tgh;
}

static void get_unlock_tgh_handle(struct gru_tlb_global_handle *tgh)
{
	unlock_tgh_handle(tgh);
	preempt_enable();
}

/*
 * gru_flush_tlb_range
 *
 * General purpose TLB invalidation function. This function scans every GRU in
 * the ENTIRE system (partition) looking for GRUs where the specified MM has
 * been accessed by the GRU. For each GRU found, the TLB must be invalidated OR
 * the ASID invalidated. Invalidating an ASID causes a new ASID to be assigned
 * on the next fault. This effectively flushes the ENTIRE TLB for the MM at the
 * cost of (possibly) a large number of future TLBmisses.
 *
 * The current algorithm is optimized based on the following (somewhat true)
 * assumptions:
 * 	- GRU contexts are not loaded into a GRU unless a reference is made to
 * 	  the data segment or control block (this is true, not an assumption).
 * 	  If a DS/CB is referenced, the user will also issue instructions that
 * 	  cause TLBmisses. It is not necessary to optimize for the case where
 * 	  contexts are loaded but no instructions cause TLB misses. (I know
 * 	  this will happen but I'm not optimizing for it).
 * 	- GRU instructions to invalidate TLB entries are SLOOOOWWW - normally
 * 	  a few usec but in unusual cases, it could be longer. Avoid if
 * 	  possible.
 * 	- intrablade process migration between cpus is not frequent but is
 * 	  common.
 * 	- a GRU context is not typically migrated to a different GRU on the
 * 	  blade because of intrablade migration
 *	- interblade migration is rare. Processes migrate their GRU context to
 *	  the new blade.
 *	- if interblade migration occurs, migration back to the original blade
 *	  is very very rare (ie., no optimization for this case)
 *	- most GRU instruction operate on a subset of the user REGIONS. Code
 *	  & shared library regions are not likely targets of GRU instructions.
 *
 * To help improve the efficiency of TLB invalidation, the GMS data
 * structure is maintained for EACH address space (MM struct). The GMS is
 * also the structure that contains the pointer to the mmu callout
 * functions. This structure is linked to the mm_struct for the address space
 * using the mmu "register" function. The mmu interfaces are used to
 * provide the callbacks for TLB invalidation. The GMS contains:
 *
 * 	- asid[maxgrus] array. ASIDs are assigned to a GRU when a context is
 * 	  loaded into the GRU.
 * 	- asidmap[maxgrus]. bitmap to make it easier to find non-zero asids in
 * 	  the above array
 *	- ctxbitmap[maxgrus]. Indicates the contexts that are currently active
 *	  in the GRU for the address space. This bitmap must be passed to the
 *	  GRU to do an invalidate.
 *
 * The current algorithm for invalidating TLBs is:
 * 	- scan the asidmap for GRUs where the context has been loaded, ie,
 * 	  asid is non-zero.
 * 	- for each gru found:
 * 		- if the ctxtmap is non-zero, there are active contexts in the
 * 		  GRU. TLB invalidate instructions must be issued to the GRU.
 *		- if the ctxtmap is zero, no context is active. Set the ASID to
 *		  zero to force a full TLB invalidation. This is fast but will
 *		  cause a lot of TLB misses if the context is reloaded onto the
 *		  GRU
 *
 */

void gru_flush_tlb_range(struct gru_mm_struct *gms, unsigned long start,
			 unsigned long len)
{
	struct gru_state *gru;
	struct gru_mm_tracker *asids;
	struct gru_tlb_global_handle *tgh;
	unsigned long num;
	int grupagesize, pagesize, pageshift, gid, asid;

	/* ZZZ TODO - handle huge pages */
	pageshift = PAGE_SHIFT;
	pagesize = (1UL << pageshift);
	grupagesize = GRU_PAGESIZE(pageshift);
	num = min(((len + pagesize - 1) >> pageshift), GRUMAXINVAL);

	STAT(flush_tlb);
	gru_dbg(grudev, "gms %p, start 0x%lx, len 0x%lx, asidmap 0x%lx\n", gms,
		start, len, gms->ms_asidmap[0]);

	spin_lock(&gms->ms_asid_lock);
	for_each_gru_in_bitmap(gid, gms->ms_asidmap) {
		STAT(flush_tlb_gru);
		gru = GID_TO_GRU(gid);
		asids = gms->ms_asids + gid;
		asid = asids->mt_asid;
		if (asids->mt_ctxbitmap && asid) {
			STAT(flush_tlb_gru_tgh);
			asid = GRUASID(asid, start);
			gru_dbg(grudev,
	"  FLUSH gruid %d, asid 0x%x, vaddr 0x%lx, vamask 0x%x, num %ld, cbmap 0x%x\n",
			      gid, asid, start, grupagesize, num, asids->mt_ctxbitmap);
			tgh = get_lock_tgh_handle(gru);
			tgh_invalidate(tgh, start, ~0, asid, grupagesize, 0,
				       num - 1, asids->mt_ctxbitmap);
			get_unlock_tgh_handle(tgh);
		} else {
			STAT(flush_tlb_gru_zero_asid);
			asids->mt_asid = 0;
			__clear_bit(gru->gs_gid, gms->ms_asidmap);
			gru_dbg(grudev,
	"  CLEARASID gruid %d, asid 0x%x, cbtmap 0x%x, asidmap 0x%lx\n",
				gid, asid, asids->mt_ctxbitmap,
				gms->ms_asidmap[0]);
		}
	}
	spin_unlock(&gms->ms_asid_lock);
}

/*
 * Flush the entire TLB on a chiplet.
 */
void gru_flush_all_tlb(struct gru_state *gru)
{
	struct gru_tlb_global_handle *tgh;

	gru_dbg(grudev, "gid %d\n", gru->gs_gid);
	tgh = get_lock_tgh_handle(gru);
	tgh_invalidate(tgh, 0, ~0, 0, 1, 1, GRUMAXINVAL - 1, 0xffff);
	get_unlock_tgh_handle(tgh);
}

/*
 * MMUOPS notifier callout functions
 */
static void gru_invalidate_range_start(struct mmu_notifier *mn,
				       struct mm_struct *mm,
				       unsigned long start, unsigned long end)
{
	struct gru_mm_struct *gms = container_of(mn, struct gru_mm_struct,
						 ms_notifier);

	STAT(mmu_invalidate_range);
	atomic_inc(&gms->ms_range_active);
	gru_dbg(grudev, "gms %p, start 0x%lx, end 0x%lx, act %d\n", gms,
		start, end, atomic_read(&gms->ms_range_active));
	gru_flush_tlb_range(gms, start, end - start);
}

static void gru_invalidate_range_end(struct mmu_notifier *mn,
				     struct mm_struct *mm, unsigned long start,
				     unsigned long end)
{
	struct gru_mm_struct *gms = container_of(mn, struct gru_mm_struct,
						 ms_notifier);

	/* ..._and_test() provides needed barrier */
	(void)atomic_dec_and_test(&gms->ms_range_active);

	wake_up_all(&gms->ms_wait_queue);
	gru_dbg(grudev, "gms %p, start 0x%lx, end 0x%lx\n", gms, start, end);
}

static void gru_invalidate_page(struct mmu_notifier *mn, struct mm_struct *mm,
				unsigned long address)
{
	struct gru_mm_struct *gms = container_of(mn, struct gru_mm_struct,
						 ms_notifier);

	STAT(mmu_invalidate_page);
	gru_flush_tlb_range(gms, address, PAGE_SIZE);
	gru_dbg(grudev, "gms %p, address 0x%lx\n", gms, address);
}

static void gru_release(struct mmu_notifier *mn, struct mm_struct *mm)
{
	struct gru_mm_struct *gms = container_of(mn, struct gru_mm_struct,
						 ms_notifier);

	gms->ms_released = 1;
	gru_dbg(grudev, "gms %p\n", gms);
}


static const struct mmu_notifier_ops gru_mmuops = {
	.invalidate_page	= gru_invalidate_page,
	.invalidate_range_start	= gru_invalidate_range_start,
	.invalidate_range_end	= gru_invalidate_range_end,
	.release		= gru_release,
};

/* Move this to the basic mmu_notifier file. But for now... */
static struct mmu_notifier *mmu_find_ops(struct mm_struct *mm,
			const struct mmu_notifier_ops *ops)
{
	struct mmu_notifier *mn, *gru_mn = NULL;
	struct hlist_node *n;

	if (mm->mmu_notifier_mm) {
		rcu_read_lock();
		hlist_for_each_entry_rcu(mn, n, &mm->mmu_notifier_mm->list,
					 hlist)
		    if (mn->ops == ops) {
			gru_mn = mn;
			break;
		}
		rcu_read_unlock();
	}
	return gru_mn;
}

struct gru_mm_struct *gru_register_mmu_notifier(void)
{
	struct gru_mm_struct *gms;
	struct mmu_notifier *mn;
	int err;

	mn = mmu_find_ops(current->mm, &gru_mmuops);
	if (mn) {
		gms = container_of(mn, struct gru_mm_struct, ms_notifier);
		atomic_inc(&gms->ms_refcnt);
	} else {
		gms = kzalloc(sizeof(*gms), GFP_KERNEL);
		if (gms) {
			STAT(gms_alloc);
			spin_lock_init(&gms->ms_asid_lock);
			gms->ms_notifier.ops = &gru_mmuops;
			atomic_set(&gms->ms_refcnt, 1);
			init_waitqueue_head(&gms->ms_wait_queue);
			err = __mmu_notifier_register(&gms->ms_notifier, current->mm);
			if (err)
				goto error;
		}
	}
	gru_dbg(grudev, "gms %p, refcnt %d\n", gms,
		atomic_read(&gms->ms_refcnt));
	return gms;
error:
	kfree(gms);
	return ERR_PTR(err);
}

void gru_drop_mmu_notifier(struct gru_mm_struct *gms)
{
	gru_dbg(grudev, "gms %p, refcnt %d, released %d\n", gms,
		atomic_read(&gms->ms_refcnt), gms->ms_released);
	if (atomic_dec_return(&gms->ms_refcnt) == 0) {
		if (!gms->ms_released)
			mmu_notifier_unregister(&gms->ms_notifier, current->mm);
		kfree(gms);
		STAT(gms_free);
	}
}

/*
 * Setup TGH parameters. There are:
 * 	- 24 TGH handles per GRU chiplet
 * 	- a portion (MAX_LOCAL_TGH) of the handles are reserved for
 * 	  use by blade-local cpus
 * 	- the rest are used by off-blade cpus. This usage is
 * 	  less frequent than blade-local usage.
 *
 * For now, use 16 handles for local flushes, 8 for remote flushes. If the blade
 * has less tan or equal to 16 cpus, each cpu has a unique handle that it can
 * use.
 */
#define MAX_LOCAL_TGH	16

void gru_tgh_flush_init(struct gru_state *gru)
{
	int cpus, shift = 0, n;

	cpus = uv_blade_nr_possible_cpus(gru->gs_blade_id);

	/* n = cpus rounded up to next power of 2 */
	if (cpus) {
		n = 1 << fls(cpus - 1);

		/*
		 * shift count for converting local cpu# to TGH index
		 *      0 if cpus <= MAX_LOCAL_TGH,
		 *      1 if cpus <= 2*MAX_LOCAL_TGH,
		 *      etc
		 */
		shift = max(0, fls(n - 1) - fls(MAX_LOCAL_TGH - 1));
	}
	gru->gs_tgh_local_shift = shift;

	/* first starting TGH index to use for remote purges */
	gru->gs_tgh_first_remote = (cpus + (1 << shift) - 1) >> shift;

}